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- Front Matter: Volume 10462
- Optical Sensing and Imaging Technology and Applications
Front Matter: Volume 10462
Front Matter: Volume 10462
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This PDF file contains the front matter associated with SPIE Proceedings Volume 10462, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.
Optical Sensing and Imaging Technology and Applications
Coarse-to-fine geometric and photometric image registration
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This paper presents a technique that performs coarse-to-fine image registration both in spatial and range domain. The goal of image registration is to estimate geometric and photometric parameters via minimization of an objective function in the least square sense. In order to reduce the probability of falling into a local optimal solution, the algorithm employs a coarse-to-fine strategy. In the coarse step, an illumination offset and contrast invariant feature detector which is named SURF is used to estimate affine motion parameters between the reference image and the target image, and then the intensity of corresponding pixels is used to directly estimate contrast and bias parameters based on RANSAC. In the fine step, the estimated parameters obtained in the coarse step are used as a good initial estimation, and photometric and affine motion parameters are refined alternatively via minimizing the objective function. Experiments on simulated and real images show that the proposed image registration method is superior to the feature-based method used in the coarse step and the groupwise image registration algorithm proposed by Bartoli.
Single-image super-resolution based on sparse kernel ridge regression
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Because they are affected by imaging conditions, aliasing, noise, etc, imaging systems are unable to obtain all of the information contained in an original scene. Super-resolution (SR) reconstruction is important for the application of image data to increase the resolution of images. In this article, an example-based algorithm is proposed to implement SR reconstruction by single-image. The mapping function between low-resolution (LR) and high-resolution (HR) images is learned by using the method of regularized regression. Then, finding the optimal sparse subset of the training data set by kernel matching pursuit (KMP). The results show that this method can recover detailed information of images, and the computational cost is reduced compared to other example-based SR methods.
Particle detection of quartz sandstone by using terahertz time-domain spectroscopy
Zhikui Wu,
Rima Bao
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In the petroleum geology field, quartz sandstone becomes one of the main sandstone reservoirs because of its preferable porosity. The particle size of quartz sandstone is related with the porosity, which has a significant relationship with oil and gas storage. It has a great significance to study the properties of quartz sandstone. In this paper, the terahertz time-domain spectroscopy (THz-TDS) system is used to detect quartz sandstones with different particle and impurities. Results show that the smaller particle is, the longer delay time is, and the smaller absorption coefficient is. In addition, chalybeate quartz sandstone reflect obviously different response in terahertz range. This suggests that terahertz technique can clearly characterize the particle of quartz sandstone indirectly reflecting the porosity of quartz sandstone and has a guiding significance for oil and gas exploration.
Denoising algorithm in dual-wavelength images of retinal oximetry using variance stabilizing transform and cross dual domain filter
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Image noise can dramatically affect image processing and hemoglobin oxygen saturation (SO2) calculation accuracy in non-invasive retinal oximetry. Recently, the denoising algorithm based on Variance stabilizing transform (VST) and dual domain filter (DDID) has been proposed to address this issue by our lab. Actually, dual-wavelength retinal images belong to multi-mode images, in order to maximize the use of complementary information between the dual-wavelength images, we further improve the algorithm. Firstly, noise parameters were also estimated by mixed Poisson-Gaussian (MPG) noise model. Secondly, a novel MPG denoising algorithm which we called VST+CDDID was proposed based on VST and cross dual domain filter. To evaluate the proposed algorithm, both simulative and real experiments have been carried out and the results show that the proposed method can effectively remove MPG noise and preserve edge details. Compared with current denoising methods based on single mode, such as VST+DDID and VST+ block-matching 3D filtering (BM3D), the proposed method shows great advantage in terms of visual quality and low-contrast detail. In conclusion, VST+CDDID can effectively use the complementary information between multi-mode images and combine the advantages of both cross bilateral filter in the time domain and Short-Time Fourier Transform (STFT) in the frequency domain. And it effectively restrained ringing effect by alternating iterative.
Research on active and passive detection for space debris
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With the increasing frequency of human space activities, the number of spacecraft and space debris on track is increasing. In order to process the information of debris after detecting it in a very short time and reduce the size, weight and power consumption of the detection system at the same time, an active and passive composite optical detection system is designed. The laser emission system in this system uses Galileo telescope system. The laser radar receiving system and the visible light receiving system are integrated in a system. These two systems share the front lens group. And they image respectively using light splitting element at the back of the front lens group. The composite system has the characteristics of miniaturization, light weight and integration. It achieves simultaneous and synchronous observation for the target. It also has good image quality and meets the design requirements.
Calibration of polarization and adjustment error of high-NA spherical surface testing in point diffraction interferometry
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In order to achieve the precision of sub-nanometer and even higher of surface testing, this paper presents a highprecision point diffraction interferometric system for high-NA spherical surface testing. The point diffraction mask as a key component is designed and analyzed in detail. The circularly polarized light is used as the light source of interferometer system to calibrate the oblique-reflection wavefront aberration introduced by the point diffraction mask. Besides, the calibration of adjustment error is a critical issue in the test of high-numerical-aperture spherical surface, and it is hard to separate the high-order aberrations introduced by wavefront defocus from the mearsured data. We present a novel calibration method based on the Zernike aberration coefficients introduced by wavefront tilt and defocus. This novel method can be carried out without knowing the actual adjustment error amount and just needs the numerical aperture of testing wavefront to solve the high-order aberrations. With the proposed calibration method, the requirement for accuracy of the mechanism and experience of operator is lowered. Experiment shows the accuracy of calibrated system is better than 0.001λ rms, which can realize the high-precision testing.
Extremally similar regions sifting for moving object segmentation in infrared videos
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It is difficult to study human actions on visual cognition as individual differences and dynamic environment causes a large number of variables. Adaptive mining the connectivity of moving human contour in infrared images based on regions can improve detecting moving object performance. We propose adaptive motion detection algorithm based on layering frequency sifting and maximally similar regions measuring in this letter, to overcome difficulties to sample moving human contour from dynamic background. First using frequency sifting layer by layer of input infrared images by Bidimensional Empirical Mode Decomposition (BEMD) representations, the original images were layered into bidimensional intrinsic mode functions (BIMFs). Thus connected edge information is remained on BIIMFs while smoothing data is filtered. Then detected connected regions using Maximally Stable Extremal Regions(MSERs) representation amongst BIMFs and the original image. Since being similarity amongst those connected regions of those images, which includes the moving human contour. At last measured similar MSERs regions hierarchically. The maximal similar connected regions segmented is candidate moving object contours. The experiment results on several open infrared videos show that the proposed algorithm improves credibility and simplicity, superior to other unsupervised measures.
A new method to estimate SNR of remote sensing imagery
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The signal-to-noise ratio (SNR) of a remote sensing image is one of the most important indicators to evaluate the quality of the image, and also can reflect the SNR performance of a remote sensing payload to a great extent. Meanwhile, the SNR determines the information precision of a remote sensing image by which researchers could use the spectral characteristics to identify the surface features. Optical remote sensing images are usually contaminated by Gaussian white noise. Surface features often interfere with each other when imaging, which increases the difficulty of SNR evaluation. For heterogeneous region, the interference between different features is stronger and could not be removed easily. For homogeneous region, same features present the same or similar characteristics, showing as similar digital number (DN) values, so the interference between same features could be removed in some way. One of the ways to remove the interference between same features is to do subtraction operation between the adjacent row DNs or column DNs in homogeneous region. And the residuals, due to subtraction, are more indicative to the noises. This paper presents a novel method for SNR estimation of optical remote sensing images. Firstly, calculating the column residuals between the same features in homogeneous region. Secondly, doing subtraction operation to calculate the row residuals between the same features in homogeneous region. Thirdly, integrating the column and row residuals to evaluate the SNR. In this paper, the new method and a traditional typical method are used to estimate the SNRs of measured images. By analyzing the results of the two methods, we can find the new one is more stable and accurate. This method provides a new way to evaluate the SNR performance of optical remote sensing payload onboard.
The improved deconvolution video restoration technology based on the infrared detection system
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The current infrared detection systems commonly memory and transfer image signals in the form of video. However, when the videos are in the process of formation, transmission and storage, they are easily polluted by motion blur and noise. Accordingly, the video motion blur recovery algorithm was proposed based on this system. Firstly, the video motion blur restoration module was built based on video streaming by integrating mutual information of every frame of sequence images. Secondly, the corresponding algorithm was put forward and the point spread function (PSF) was estimated effectively. Thirdly, the motion blur recovery process was described and all the function module were created. And then, in order to reduce the calculation burden, the image sequence was equal interval sampled from the original video, which enhancing the image quality and achieving better restoration effect. Finally, a subjective and an objective evaluation system were introduced to compare our algorithm with two other classical algorithms and evaluate results. The experimental results show that the peak signal-to-noise ratio of each frame of restored video reached 37, mean square error was below 9, which was superior to the control algorithm. The results basically meet the requirements of detection system, which discovering targets and monitoring the airspace.
Bayesian multi-frame super-resolution of differently exposed images
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This paper presents a technique that performs multi-frame super-resolution of differently exposed images. The method first employs a coarse-to-fine image registration method to align image in both spatial and range domain. Then an image fusion method based on the maximum a posterior (MAP) is used to reconstruct a high-resolution image. The MAP cost function includes a data fidelity term and a regularized term. The data fidelity term is in the L2 norm, and the regularized term employs Huber-Markov prior which can reduce the noise and artifacts while reserving image edges. In order to reduce the influence of registration errors, the high-resolution image estimate and registration parameters are refined alternatively by minimizing the cost function. Experiments with synthetic and real images show that the photometric registration reduce the grid-like artifacts in the reconstructed high-resolution image, and the proposed multi-frame super resolution method has a better performance than the interpolation-based method with lower RMSE and less artifacts.
Hyperspectral face recognition based on spatio-spectral fusion and local binary pattern
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With the optical sensing technology development, the hyperspectral camera has decreased their price significantly and obtained better resolution and quality. Hyperspectral imaging, recording intrinsic spectral information of the skin at different spectral bands, become a good issue for high performance face recognition. However, there are also many new challenges for hyperspectral face recognition, such as high data dimensionality, low signal to noise ratio and inter band misalignment. This paper proposes a hyperspectral face recognition method based on the covariance fusion of spatio-spectral information and local binary pattern (LBP). Firstly, a cube is slid over the hyperspectral face cube, and each cube is rearranged into a two-dimensional matrix for each overlapping window. Secondly, covariance matrix of each two-dimensional matrix is computed to fully incorporate local spatial information and spectral feature. Thirdly, the trace of each covariance matrix is calculated to replace the pixel values of the fusion image in the corresponding location respectively. Finally, LBP is applied for the fusion hyperspectral face image to get final recognition result. The hyperspectral face recognition is tested on Hong Kong Polytechnic University Hyperspectral Face database (PolyUHSFD). Experimental results show that the proposed method has higher recognition rate (90.8%) and lower computational complexity than the state of the art hyperspectral face recognition algorithms.
Identification of conveyor belt injury based on image texture SVM classification method
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In the field of steel wire core conveyor belt detection, the X-ray detection method has been widely used for its accuracy and reliability. But as a result of the monotonous, baldness and plenty of X-ray image, it is necessary to apply the computer image processing techniques to identification wire injury accurately and automatically. Then the injury can be located in the actual conveyor belt to maintenance and repair. And the joint is an important part of the conveyor belt, for it is easy to recognize in the practical application, so as the benchmark to joint reference point positioning fault is a good choice. Therefore, the accurate identification of joint is very important to conveyor belt injury locational. At present there are some algorithms applying the method of detecting domain gray level or horizontal gradient change frequency in the identification of joint. These algorithms can be accurate to single image of joint without considering the practical complex and changeable X-ray image for the different thickness of the conveyor belt outer rubber. For single image characteristics of the proposed algorithm is easy to failure in practical application. A new robust algorithm is necessary to solve this problem. And SVM(Support Vector Machine) is a novel method of machine learning evolving from Statistics. SVM presents many own advantages in solving machine learning problems such as small samples, nonlinearity and high dimension. In this paper, the image texture SVM classification method construct feature vectors through the extraction of image gray level co-occurrence matrix texture information. classified feature vectors using the SVM classification method to determine whether the image contains joint and provide the joint location information. The mentioned texture information include gray-level co-occurrence matrix energy, contrast and entropy. And the gray level co-occurrence matrix reflects the image direction, adjacent interval and the change in value of integrated information. SVM classification method is applied to locate the joints number and position on the real conveyor belt. And by means of image binarization, skeleton and such as pretreatments, this paper use the method of template matching for the identification wire fracture. Finally the method locate injury on the real conveyor belt according to the fracture position and joint position of the pixel distance. The results show that the image texture SVM classification method can effectively combine the method of template matching for the identification of conveyor belt injury.
Target interpretation of visible light image and infrared image fusion method
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Due to the different purposes of image fusion, fusion approach taken is also different. For target identification, as a result of target feature of infrared and visible light image is different, in order to keep the high spatial resolution and rich texture information of visible light image, At the same time, make the target in the infrared image as prominent as possible. This paper uses a fusion algorithm based on Non-Subsampled Contourlet Transform (NSCT) and wavelet transform. After image NSCT decomposition, use of low frequency coefficient fusion algorithm based on wavelet transform, according to the characteristics of the fusion image the high frequency coefficients using the fusion rule based on region energy. The experimental results show that the fusion algorithm can keep the Spectral information of visible light image and the target information of infrared image better, with more details and clearer edges. The algorithm can obtain an ideal fusion image, which has a guiding effect on the target's interpretation, and its fusion effect is better than the conventional image fusion algorithm.
Denoising processing of MIE-polarization lidar signal using wavelet
Hui Yang,
Xuesong Zhao,
Jiesong Ye,
et al.
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The echo signal of MIE scattering and polarization lidar is contanminated by the noises including background noises and detector noises, there exist obvious difference in fourier spectrums of original signals and denoised signals at high frequency parts. In this paper, a new method of lidar signal denoised by scattering wavelets was proposed, and original PRR signals of lidar were denoised by different wavelet basis. The experimental results showed that:1) Daubechies 4 wavelet basis (db4) met the requirements of denoising; 2)wavelet denoising could better preserve peak features of lidar echo signal than moving average method; 3) the original and detailed characteristics of atmospheric aerosol extinction profile was maintained, and the accuracy of atmospheric aerosol extinction coefficient inversion was improved. For lidar echo signals with low SNR, this method improved data processing method of Mie-scattering and polarization lidar and improved the accuracy of the retrieval of atmospheric aerosol extinction coefficient, the signal contamination from electric noise and the background light noise can be reduced by the proposed wavelet method.
A method of gaze estimation for wearable multi-camera devices using stereo vision
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An approach to gaze estimation for wearable devices is proposed and its effectiveness is demonstrated. The proposed approach includes composing stereo vision system which is comprised of half transparent and half reflecting mirror and multi-camera, and its calibration procedure is easy and practical. This whole system can also run online and with little intervention from user by using half transparent and half reflecting mirror, and cameras above the eyes. Because of the application of stereo vision system, some feature points in the region around eyes can be solved. Thus, eye gaze is estimated directly by calculating the spatial coordinates of feature points which are extracted from pupil and eye corner. The calibration procedure is general, as no complex model of the human eye is utilized in this work, and it can be demonstrated as how to calibrate the angle between optical axis and directly measured gaze. The proposed approach is effectively to study visual attention with the help of gaze estimation experiments, and it is useful and practical for people operating in unstructured scenarios.
Design and implementation of multi-spectral multi-axis parallel calibration system
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A variety of environmental detecting and perception of equipment are equipped in high integrated systems such as unmanned vehicle, unmanned aerial vehicles, and intelligent robot and so on. The equipment include laser radar, television observation device, infrared observation device and low light level observation device and so on. In order to ensure the effective fusion of multi-spectral information of multiple devices, all the optical axis of different spectrum equipment must be parallel, or the initial zero of the optical axis must be parallel. The locations of different spectral equipment in system are different, some optical axis are far apart. To achieve the goal of all-weather, arbitrary geographical conditions detecting multi-optical axis parallelism of different spectral, multi-spectral multi-axis parallel calibration system is designed. In the calibration scheme, the infrared axis is used as the first benchmark axis, and adjusts the multi-spectral parallel light pipe to parallel to the infrared axis. Then multi-spectral parallel light pipe is used as second benchmark axis to detect the parallelism of light axis of TV, low light level observation device, and laser radar. In the process of system design, on the premise of guarantee accuracy, the indicators of the parts are fully demonstrated, and the maneuverability and adjustability of the system are considered. Through the steps of design, processing, assembly and debugging, the multi-spectral multi-axis calibration system is realized. After by testing the multi-optical axis parallelism in integrated system, it is reflected that the multi-spectral multi-axis calibration system has the characteristics of reasonable design, easy to operate. And it is able to achieve rapid and high resolution multi-spectral multi-axis parallel calibration under all-weather and arbitrary geographical environment.
Objective lens design of polarization imaging in haze environment
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Nowadays, haze environment has a severe impact on astronomical ground-based space observations, which leads to the decline of imaging quality radically. In this article, the impact on the ground station caused by haze environment has been analyzed. In order to improve the imaging quality of the observation target, an optical system has been designed using perspective polarization imaging techniques. To ensure the precision of polarizing measurement and quality of wide field imaging, We analyzed the design of the polarizing of the objective lens and the difficulties of the structure of the system. Finally we have designed a reversed telephoto telemetric structure in the image space successfully. Improved entrance light and achieved the performance indicators to the field of 44.3 °, f # 4, back focal length 2 times the focal length, focal length 20mm. The experiments of the system proved to be successfully improved the imaging quality compared with the traditional imaging system.
A fast approach against large foreground motion in real-time image stabilization
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Handheld electro-optical imaging devices usually suffer from shaky problems. In this paper, we present a fast robust approach for real-time image stabilization. Since the perform1ance of image stabilization mainly depends on global motion estimation and the accuracy of motion estimation will be affected when foreground motion happened, sudden image jitters will be introduced during stabilization. To solve this problem, conventional methods detect and remove the foreground objects in motion estimation but this way works inefficiently and fails when foreground moving objects occupy large part of image. Our method is based on the following improvements: modified ORB feature points(FPs) processing, adaptive calculation of affine transformation matrix and joint utilization of two Kalman filters. It can solve the sudden image jitter problem even when there are large foreground moving objects in the image. Qualitative and quantitative evaluations demonstrate the merits of our method. Experiments show that our method solves large foreground motion problem and achieves 35 FPS for 640*480 image on Intel Core i5-4590 CPU@3.30 GHz on the windows.
Long focal length large aperture optical passive athermalization MWIR optical system
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In this research, we designed an MWIR optical system, which is equipped with long focal length, large aperture, optically athermalization. The optical system has been athermalized under wide temperature range (-40 to 70 DEG C) by means of optically passive compensation of more two-optical-material and one housing material combination. The optical system only is composed of six lenses, the transmission of the optical system is high. The final optical system has a 1200mm focal length and a 0.46°×0.37° field of view. The modulation transfer function of the optical system is close to the diffraction-limit, the 4-bar target image of the MWIR imager is very legible. The design and test results show that the image quality of the optical system is perfect, and it can meet the requirements of the high definition and high performance MWIR imager and needn't focus from minus 40 degrees centigrade to positive 70 degrees centigrade.
Discussion on the optimal deconvolution for electro-optical imaging systems
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Ringing Artifacts are the most challenging problem in image restoration. However, the source of ringing is still in suspense. This paper investigates the source of ringing by focusing on the mathematical principle of deconvolution with the degraded model. From continuous sampling to undersampling, the essential causes of ringing appearance are discussed through theoretical derivation and quantitative analysis. Based upon the discussion above, the optimal deconvolution for electro-optical imaging systems is put forward to achieve ideal balance between ringing suppression and sharpness enhancement. Comparison results show the superiority of the proposed optimal filters.
Dual channel and fast response optical fiber temperature detection system based on Raman scattering
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In order to monitor the early fire situation caused by coal spontaneous combustion or cable aging, cable heated, cable overcurrent and other reasons, a dual channel and fast response temperature detection system is designed based on the Raman scattering principle in which anti-stokes signal in back Raman scattering is sensitive to temperature. The performance of the temperature detection system is obtained through experiments. The experimental data shows that the maximum error of temperature measurement is 0.7°C, the stability is 1°C in 30 minutes when both channels carry 2.5km sensing fiber, single channel response time is less than 17s and position-calculated error is less than 2m. This system would have a good application prospect in distributed fire detection and early warning under mine.
Salt-and-pepper noise removal in polarization optics imaging
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In the target detection process of polarization optics imaging, due to the turbulent effect of the target signal transmitted in the atmosphere and the photoelectric conversion of optical imaging sensors and other factors, Salt-and-Pepper noise which affects the detection accuracy. According to the statistical characteristics of the Salt-and-Pepper noise probability density, a new structure preserved polarization image Salt-and-Pepper noise removal method is proposed. With the new signal sparse representation theory and image inpainting method, only the noise regions is restored by the noise point detecting. In the inpainting process, the structural similarity is considered which can improve the structural information retention ability of polarization image. Numerical simulation results demonstrate the validity of the proposed method both subjectively and objectively.
Design of a visible optical passive ranging system based on micro main board
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A design scheme of a visible optical passive ranging system based on micro main board was presented. In this system, all the software logic including the passive ranging algorithm based on target feature size was concentrated on the computer motherboard. The hardware part only completed the function execution and physical support, which could greatly improve the product integration degree, and reduce the volume and weight of the product. The system mainly included high definition imaging sensor unit, active laser night vision unit and signal processing unit. Through the design of hardware and software, the system could realize passive ranging. The system adopted the 980nm laser night vision technology which is invisible to the human eyes. The technology with good concealment could realize the image situation awareness and information acquisition at night. Through passive ranging experimental verification, the ranging accuracy of the system prototype was less than 10%. With the current hardware configuration parameters, the ranging distance to the person was more than 1km with good robustness and stable performance. The actual engineering practice can be widely used in all-weather situation awareness and optical passive ranging of target.
Design of inspection system for surface defects on industrial parts under complex background
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This work aims at detecting defects on metallic industrial parts with complex surface. The searched defects are scar, rust and inclusion. A specific inspection system has been designed to deal with the particular inspected surface features. In the system, two images are acquired with the help of multiple light sources and CCD color digital camera. Based on the traditional algorithm, the background removal algorithm is designed in this article, and the color image feature extraction is also used for auxiliary analysis. A thresholding processing is then applied on this image in order to segment the imperfections. The perimeter and area of defects are calculated to further identifies the characteristics. The developed inspection system has been tested and it can accurately detect the defects of industrial parts with complex background. The recognition rate of algorithm is more than 96%.
LOS stabilization model for ship swaying based on subdivision iterative algorithm
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Shipboard optical measurement equipment is affected by ship swaying, and a fixed order, such as “yaw, pitch and roll”, is always adopted to realize the mutual conversion between the earth reference frame and the deck reference frame. This paper simulates the solving model on six different coordinate transformation orders, finds that its error is great and it will affect the shipboard optical measurement equipment’s pointing precision of LOS (line of sight), so we put forward a LOS stabilization model based on subdivision iterative algorithm. Through the simulation and analysis, the new model can let all coordinate calculation value of different switching sequence converge to the true value, and it will improve the accuracy of existing solution model. The method is significant to improve the tracking control accuracy and data processing precision of angular measurement.
Spectrum analysis on geological profile: a case study of Luzong area in Anhui China
Lin Liu,
Jiachun Guo
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In order to further research the geological composition by spectral reflectance characteristics in Luzong area, this study was performed. Using ASD spectraradiometer (FieldSpec-FR), the spectra from multiple profiles were collected, the distance of 100cm from the testing surface was used. The spectral curves were smoothed with the moving average method, and the continuum removal was conducted to highlight features of optical absorbance. Each spectral curve gave the main characteristic composition of the profile, and the spectral curves from different profiles were compared and analyzed, some typical differences could be obtained obviously. All the profiles in the study area saw some similar spectral behavior: there were absorbing valleys at 900 1450 1900 2200nm, but the number of absorbing valleys and the bandlength of them were a little different .That is to say, the main structure and component can be obtained by testing spectrum without the help of other professional testing equipment. Using spectral analyst tool of ENVI 5.0 to give a comprehensive score, several minerals obtained high score, some of them clearly inconsistent with the actual were excluded, then the main minerals of the profiles were finalized, and which were consistent with those given by geological materials. For some profiles, the main composition and the relative proportion were also calculated out by the method of linear spectral decomposition, these results gave detailed components of the selected profiles, which had higher value and reliability than the former. Thus the differences between these profiles were also found. Another aim of this paper was to study the method to inversion material compositions and try to provide some useful references for spectrum analysis. Furthermore, through detailed analysis on the results, it was also found that the measuring distance of 100cm from testing surface was still effective in field spectrum survey, the main structure and component could be obtained by these testing spectra. In order to grasp the nature of things quickly, a larger distance is feasible and necessary, macroscopic geological structure was provided quickly and accurately, which was not affected by local and microscopic interference. Unfortunately, there were some detail information lost, and the testing effect of 10cm from the testing surface will also be analyzed deeply in future.
An improved high-accuracy centroid detection method for Shack-Hartmann wavefront sensor
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The accuracy of Shack-Hartmann wavefront sensor is mainly depended on the accuracy of the centroid detection measurement. The traditional method of exclusively using detection window method or threshold method cannot reduce the noises that affect centroid detection extremely. In order to improve the accuracy of Shack-Hartmann wavefront sensor to achieve high-precision wavefront detection of adaptive optics systems, we proposed an improved centroid detection method. Morphologic method is used to separate the spot signal from the noise primarily, median filter and threshold method inside the detection window are adopted to reduce the noise inside the detection window. For a spot image with noise, the centroid detection error has been decreased to 0.0395pixel by the method in this paper. Compared with the traditional detection window method and threshold method, the accuracy of centroid detection has been improved by 96.15% and 45.59%. The simulation results demonstrate that this method can significantly improve the accuracy of centroid detection.
Sea ice features extraction near the South Shetland Islands with Sentinel-1 SAR data
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Antarctic sea ice is a sensitive factor to global climate changing. Study the sea ice changing laws is useful to choose the safe routes for the scientific investigation and merchant ships. South Shetland Islands adjacent sea is an important krill fishing area, it could be beneficial to choose the suitable days and routes to know the sea ice distribution and moving features in fishing seasons in advance. SAR data has the advantage of better penetrating ability than visible and infrared bands remote sensing data, they are more suitable to detect Antarctic sea ice than optical remote sensing data. A series of imagery pre-processing steps were carried out, including heat noise removing, radiometric calibration, speckle filtering, geo-coding, projection transformation, subarea clipping. Threshold method was carried out to detect sea ice, and 24 sea ice distribution maps were gotten from December 2015 to February 2016. Then sea ice concentration were calculated based on the sea ice extraction results maps, and sea ice changing law were analyzed in the South Shetland Islands adjacent sea area. Multi-polarization SAR data is more beneficial to improve the sea ice detection accuracy in the Antarctic sea area.
Study of infrared and UV dual color warning system based on lobster-eye optics
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In this paper, we introduce a new method for infrared and UV double color warning system. To increase the recognition ability of enemy targets, the warning system should detect the multiple radiation wave band characteristics of the target at the same time. The optical lens are based on lobster-eye optical system, which could get a large field of view through reflecting. The double color detection is based on AlGaN materials and reasonable band design. In the text, we will give the simulation of the lobster-eye lens and optimize the basic structure of the detectors. The main difficulties for the practical use of the system are also introduced.
Research of ship scene simulation based on SE-Workbench-EO
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SE-Workbench-EO as an advanced platform of IR scene simulation was introduced. The methods and application of ship IR scene simulation were studied based on SE-Workbench-EO. An infrared scene model of the ship target with the atmosphere and sea surface background is set up. Based on this model, the infrared radiation of the ship scene in the wavebands of 3-5μm and 8-12μm is analyzed. A complete process is achieved which contains model analysis, scene modeling and infrared imaging. It provided references to the infrared scene simulation of the ship and other targets.
Design of 1024x3 ROIC with TDI for scanning type IRFPA imaging
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Design of a multispectral infrared focal plane array ROIC (readout integrated circuit) with TDI (time delay integration) is presented. A 3 SNR improvement can be achieved by a 3 pixels TDI implementation. The 3 pixel signals in each channel are firstly integrated by 3 CTIA structures, then the TDI action is in SC-AMP (switch capacitor amplifier) of each channel. A novel switch capacitor amplifier topology is proposed which can both reduce power dissipation by shutting down the AMP and realize offset voltage cancellation. Besides, bad pixel replacement is realized by an alternative gain of the SC-AMP. The proposed ROIC can work well both room and cryogenic temperature. Simulation results show that the CTIA input stage have a good linearity of 99.721% (post-layout sim) over 2.8V output span.
3D discriminative feature selection for mid-level representation
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Discriminative feature representation is significant for boosting the performance of computer vision tasks covering different levels. Traditional low-level feature representation exhibits good generalization and robustness while lacks of enough discriminant ability. In this paper, we focus on 3D local shape features, proposing a discriminative feature selection method, which is also closely related with mid-level 3D shape representation. We firstly design a histogram-signature hybrid 3D local shape descriptor using 3D geometrical information from the 3D point cloud of a tested object. Then, we propose a discrimination power metric to automatically select a collection of discriminative local shapes from a candidate set, resulting in a mid-level shape feature representation. The proposed algorithm is applied in the task of multi-view 2.5D scan registration. The performance was verified on public and popular instance-level 3D object datasets. Both qualitative and quantitative results demonstrate the effectiveness and robustness of the proposed algorithm on different 3D objects. Compared with low-level 3D object representation, the discriminative feature selection for 3D shape feature representation allows for superior performance with higher precision and recall rate.
Laser radar range profile analysis and simulation
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In this paper, laser radar range profile theory and simulation method are investigated. Laser radar range profile theoretical formula is given based on the theory of Gaussian laser beam, BRDF, and target shape. On the purpose of simulating the range profile of certain targets, the geometrical 3D models of some simple and complex objects are constructed respectively, and then the viewpoint coordinate and target coordinate are established. The location information of vertexes and facets can be obtained and exported to utilize. In next step their laser radar range profiles in many postures are acquired and compared sequentially. The influences of Gaussian pulse width, target shape, size and transmit-receive angles on the simulation results are discussed. In this way this paper can provide theoretical and simulation methods and bases for extracting target features and recognizing targets using laser radar range profiles.
Object tracking via Spatio-Temporal Context learning based on multi-feature fusion in stationary scene
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A robust algorithm is proposed for tracking object in dynamic challenges including illumination change, pose variation, and occlusion in stationary scene. To cope with these factors, the Spatio-Temporal Context learning based on Multifeature (MSTC) is integrated within a fusion framework. Different from the original Spatio-Temporal Context learning (STC) algorithm which exploits the low-level features (i.e. image intensity and position) from the target and its surrounding regions, our approach utilize the high-level features like Histogram of Oriented Gradient (HOG) and low-level features for tracker interaction and selection for robust tracking performance in decision level. Experimental results on benchmark datasets demonstrate that the proposed algorithm performs robustly and favorably against the original algorithm.
Violent video detection based on MoGLOH feature
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Violent detection from video is a hot topic which has wide application. The aim of this paper is to design a novel feature descriptors called motion gradient location and orientation histogram (MoGLOH), which encode not only the local appearance but also explicitly models local motion. Our proposed MoGLOH is composed of two part of information. The first part is the gradient location and orientation histogram (GLOH) describing the spatial appearance, and the second part is an aggregated histogram of optical flow with a log-polar location grid named Optical Flow Orientation Histogram (OFOH) which indicate the movement of feature point. To eliminate the feature noise, the non-parametric Kernel Density Estimation (KDE) is employed on the MoGLOH descriptor. The theoretical analysis demonstrates the proposed algorithm performs robustly and favorably.
On the evaluation method of anti-ship missile against passive compound jamming
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In this paper we analyze the working principle of passive compound jamming anti-ship missile, study the operational method of the radar/infrared imaging composite guidance anti-ship missile against passive compound jamming, and describe the anti-jamming capability of anti-ship missile by establishing multi dimension index system . Comprehensive evaluation method is applied to evaluate the anti-ship missile against passive compound jamming, so that the gained conclusions are of guiding significance to improve the anti-jamming ability of anti-ship missile.
A star image registration algorithm based on joint feature matching
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With the amount of space debris increasing accordingly with human activities in near space, the threat of space debris to space missions raises the concern of surveillance of these malicious targets. Space target detection based on optical image is a feasible and effective solution for monitoring these malicious targets. However, as the observation platform is nonestationary, image obtained from the telescope need registration for further operation. In this paper, a star image registration algorithm based on joint feature matching is proposed. The star images are firstly denoised by filtering system. Then reference stars are preselected and their features are constructed. By matching the extracted features, a pool of star pairs is established. Transform parameters are derived from the locations of these matched pairs. Experimental results have validated the capability of our algorithm in pixel accurate star image registration.
Correction of over-exposure using dark channel prior and image fusion technique
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A novel over exposure (OE) correction method using Dark Channel Prior and image fusion technique is proposed in this work. Assuming an OE image can be modeled as a normal exposure image added up with a layer of asymmetrical haze, its submerged information in OE regions is enhanced by haze removal model. With image fusion technique, the obtained texture in OE regions is used to restore the over exposure. Experiments show that our method works well in submerged information restoration without increasing pseudo-information and over Saturation.
Design of a four-quadrant detector for the laser seeker of guided gun-launched projectile
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The design of a four-quadrant detector for the semi-active laser seeker on the guided gun-launched projectile was studied. Several key parameters of the four-quadrant detector, including the photosensitive area, spectral responsivity, respond speed and noise equivalent power were discussed in the application. A bigger photosensitive area will be benefited to get a larger detection range, however, it will decrease the response speed and increase the positioning time. The spectral responsivity of the detector was chosen to be highly sensitive with the 1064nm wavelength laser, and its responsivities for the other wavelengths were relatively low. As the operation time is short, the response speed of the detector need to be increased as higher as possible, and many influencing factors were compromised in the design. A lower number of NEP was optimized for the better detecting capability. The orientation detection circuit and related positioning algorithm was developed to determine the yaw angle and pitch angle between the projectile and the target. Then the relative position errors, including the lateral and vertical deviation, were obtained from the four-quadrant detector. The influence of the size of facula with respect to the detecting sensitivity and effective measure ranges of the four-quadrant detector were analyzed. Finally, the sizes both of the facula and the four-quadrant detector were designed to ensure the most efficient use of the detecting sensitivity and effective measure ranges of the detector.
Adaptive neural network non-uniformity correction algorithm for infrared focal plane array based on bi-exponential edge-preserving smoother
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In this paper, a new algorithm for non-uniformity correction of infrared focal plane arrays based on neural network and bi-exponential filter is proposed. Due to the edge preserving property of bi-exponential filter, the algorithm can estimate the gain and bias coefficients at the strong edge more accurately, thereby suppressing the ghosting effect. In order to suppress the blurring effect, a motion detection is carried out before the correction coefficients are updated. A motion evaluation index based on the L1 norm of the temporal variation of the image and the image roughness is designed to improve the accuracy of motion detection. Moreover, an adaptive learning rate calculation method is proposed, which makes the learning rate larger in the image smoothing region and smaller in the edge region. This results in a faster convergence in a uniform region of the image , and it is not easy to cause a correction coefficients estimation error in the edge region. Several infrared image sequences are used to verify the performance of the proposed algorithm. The results indicate that the proposed method can not only preserve the details of the image, but also reduce the non-uniformity. Besides, it has a good inhibitory effect on the phenomenon of ”ghosting” and ”blurring”.
Method for reducing the degradation effects of EMI wire grid on the optic performance
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The mechanism of the image degradation due to the opaque metallic wire grid is analyzed and a degradation mode is built based on the theory of Fourier optics. The effect of different opaque wire grid on the image quality is simulated. We define the manner of using wire grid that will meet system requirements for both optical and shielding efficiency. A gray non-uniformity correction model based on two-point correction method is built, and the way to estimate the degradation function and the restoration process are proposed. Both the experimental results and simulation show that the non-uniformity of the image after correction is less than 1/10 of that of before correction and the relative error between the original image and restored image is 0.56%.
Dispersion compensation of linear frequency modulated wave based on SSB modulation and pre-distortion
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In microwave photonic radar systems, the generation and transmission of linear frequency modulated wave (LFMW) are influenced by dispersion in the optical systems and devices. As the bandwidth of LFMW used in radar systems becomes greater, the effect of dispersion on wideband optical signal cannot be ignored and should be well compensated. Traditional compensation methods of dispersion in optical systems are facing difficulties when dealing with high order dispersion and wideband signals with demand of precise frequency control. This paper proposed a method of dispersion compensation for wideband LFMW transmission in optical systems with dispersion, based on single-side band (SSB) modulation and pre-distortion, and the linear mapping from time to frequency of LFMW. Dispersion of the transmission systems is measured to calculate the pre-distortion of LFMW. Then the single frequency laser is SSB modulated by microwave LFMW in amplitude to remove the influence from dispersion on the envelope, and the LFMW is predistorted with the calculated results in generation. In the proof-of-concept experiment, an LFMW with period of 10 us, pulse width of 8 us and instantaneous frequency from 8 GHz to 12 GHz is modulated on the laser with wave length of 1550 nm, and transmitted in dispersion fiber or devices. Second order dispersion of about 1713 ps/nm introduced by dispersion fiber is compensated in experiments. Third and fifth orders dispersion introduced by an equivalent electronic filter are compensated, and 44% improvement of the linearity of frequency modulation after compensation is obtained in the experiment.
Design of a bulk acoustic wave filter for wi-fi band
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In order to ensure the normal operation of mobile devices in the Wi-Fi band without interference from adjacent frequency bands, a BAW filter for the Wi-Fi 802.11b band (2402-2482 MHz) is designed. An initial structure ladder filter based on a one-dimensional Mason equivalent circuit model of thin-film bulk acoustic resonator (FBAR) is designed. The resonance area value of series FBARs and the ratio of resonance area value of parallel FBARs to series FBARs are made into two types of optimization parameters reasonably. According to the required insertion loss and out of band rejection of filter as the optimization objective, the optimized values are obtained by the algorithm based on gradient and genetic in ADS software. In order to make the simulation results more accurate, the combined acoustic-electromagnetic method is used to simulate and compare with the simulation results of the Mason equivalent circuit model in the filter design process. The results show that the performance of the filter is decreased, insertion loss increased 1.6 dB, ripple increased 1.1 dB, out of band rejection is basically the same. The design of Wi-Fi band BAW filter has low insertion loss (less than 3 dB) and high out of band rejection (more than 40 dB) performance.
Analysis on gamma irradiation sensing mechanisms of thin film bulk acoustic resonators
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Experiment shows that thin film bulk acoustic resonator (FBAR) is feasible to detect gamma irradiation, but the sensing mechanism is not studied deeply. For this problem, different sensing mechanisms are proposed to explain the resonance frequency shift after gamma irradiation according to two different FBAR structures. One FBAR structure is four - layers stacked (metal layer - piezoelectric layer - oxide layer - metal layer). After gamma irradiation, a voltage will be formed in the radiation sensitive layer (oxide layer), which is equivalent to impose a DC voltage to the piezoelectric layer that makes resonant frequency shift. There is a semiconductor layer between oxide layer and piezoelectric layer in the other FBAR structure, which is the difference between the two structures. A voltage formed in the oxide layer after irradiation will change the surface potential of the semiconductor and then change the space charge layer capacitor in semiconductor that makes the resonant frequency shift. The results of two mechanisms are obtained by simulation and compared with those in related literature, it is found that the trends and magnitudes of frequency shift are the same, so the two mechanisms are feasible.
Automatic position and guidance system for space manipulator operation based on videometrics
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Based on the principle of videometrics, this paper presents a visual positioning and navigation system for lunar soil sampling and encapsulation. The system uses local histogram technique to decrease the influence of complex light environment and sub-pixel correlation technique of camera measurement is used to overcome the influence of low resolution of monitor camera and improve the precision of measurement. It can provide pose parameters for space manipulator operation.
High precision measurement method of laser divergence angle based on CCD imaging
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The use of CCD imaging to measure laser divergence angle and imaging spot quality directly affect the accuracy of measurement results. Analysis of laser spot imaging features, do noise reduction and desaturation process for the image. With the method of image coordinate vectors superposition to obtain the laser intensity distribution curve in x, y direction, and laser spot diameter is exactly calculated by curve fitting algorithm. Experiment for different exposure intensity spot images, this method is effective to suppress the influence of CCD self-noise and improve measurement accuracy. Different exposure intensity spot images obtained a high measurement accuracy results, and laser divergence angle measurement results with an accuracy higher than 0.01mrad.
Nonlinear changes of chlorophyll-a fluorescence with laser induced saturation
Xiao-long Li,
Fei Yu,
Yong-hua Chen,
et al.
Show abstract
Laser induced fluorescence (LIF) is a common technique for measuring chlorophyll-a (Chl-a) concentration in water, and is able to obtain profile distribution. The natural water body is a turbid media for laser transmission, resulting in a great attenuation of luminance in a short distance. Increasing laser intensity is often considered an effective way to probe deeper. However, it has been found that there is a non-linear relationship between fluorescence intensity of Chl-a solution and laser energy which may causes laser-induced saturation of fluorescence with measurement conditions unchanged. Thus, the saturation effects of Chl-a fluorescence at 685 nm were studied at two aspects, namely, Chl-a concentration and the intensity of excitation pulse. In the experiment, several concentrations of Chl-a solution were measured by 355 nm laser. For a fixed Chl-a concentration, the intensity of fluorescence gradually becomes to worse following the intensity of excitation pulse raised, while the ratios of Raman intensity of water to pulse intensity correspond to a good linear relationship. On the other hand, with different energy densities of excitation laser, the variations of Chl-a fluorescence intensity were analyzed by non-linear curve fitting. For higher Chl-a concentration, the lower threshold value of excitation intensity can lead to the nonlinearity of induced fluorescence intensity versus laser intensity. Here, the nonlinear changes of Chl-a fluorescence with saturated excitation are studied for supporting the measurement of oceanographic fluorescence by LIF and correctly estimating chlorophyll concentrations.
Design of flame detection video camera system based on DSP
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In order to alarm the fire and analyze the material burned, the high efficiency imaging system is designed to monitor the fire. The system selects the high performance CMOS image sensor, utilizing real-time DSP with higher computing power, it is designed based on DSP C6748 by IIC serial port flame detectors video camera’s registers, and the generated image data sent to DSP by VPIF interface, the image algorithm is transplanted to DSP, at last, the system will alarm the fire and output spectral characteristics of the burning material via Ethernet interface. This system completes algorithm hardware realization, and the algorithm can detect image in real-time and extract the effect of spectral characteristics of burning material, so that the algorithm processing can speed up from minute level on the PC to the sub-second level.
A terahertz image super-resolution reconstruction algorithm based on the deep convolutional neural network
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Nowadays with the growing threat of terrorist attacks throughout the world, effective security technologies are of urgent need to protect crowds and critical infrastructure. Terahertz wave has emerged as a more powerful tool in security. Terahertz wave is able to penetrate dielectrics such as plastic and cloth so as to detect weapons and contraband hidden under people's clothing without harming human bodies. Nevertheless, image obtained in this frequency range is pretty poor because the diffraction at their relatively long wavelength cannot be ignored in such case. In this paper, we shall briefly introduce the high-resolution (HR) reconstruction for terahertz imaging utilizing the ideology and methodology of super-resolution (SR) restoration in image processing which aims at recovering a high-resolution image from a single low-resolution image. Through the preliminary feasibility research, we applied the image super-resolution algorithm based on the deep convolutional neural network (CNN) to the single passive terahertz image reconstruction. Our deep CNN demonstrates state-of-the-art restoration quality and achieve fast speed as well. Our results indicate that the processed passive terahertz images have clearer edges as well as outlines and are easier to identify suspicious items than the original ones. On the whole, our method outperforms other methods such as the interpolation method and the learning-based image super-resolution reconstruction algorithm. The results indicate a promising prospect for HR terahertz imaging reconstruction.
Visibility-enhanced dual-band infrared image fusion based on nonsubsampled contourlet transform
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In this paper, a new dual-band infrared image fusion for enhancing visibility is proposed. Before proposing the new algorithm, we studied the human visual systems and found that human visual systems have directional characteristics, and the sensitivity of the human eye to the phase angle is higher than the change of the mode. Considering these characteristics of human visual systems, we put forward a dual-band infrared image fusion algorithm based on local window activity measure. First, the mid-wave and long-wave infrared source images are decomposed into the multi-scale and multidirectional subbands by using a nonsubsampled contourlet transform(NSCT) method. Then, the highpass subbands are fused by selecting the maximum absolute operator and the lowpass subbands are fused by using a method based on region energy and region variance. Finally, the image is reconstructed by inverse nonsubsampled contourlet transform and a fused image is obtained. We use a dual-band infrared camera with common optical path to acquire images for the fusion experiment. The method is compared with the gradient pyramid transform and the wavelet transform in fusion effectiveness. From the comparison of the evaluation parameters, we can find that the fusion results of the proposed algorithm are better than other algorithms, and this visibility-enhanced dual-band infrared image fusion algorithm based NSCT is more suitable for human eye observation and understanding.
Transmission characteristics of terahertz laser in underdense plasmas generated by DC discharge
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In this paper, terahertz (THz) characteristics of a direct current (DC) arc discharge uniform plasma are analyzed, which is of practical significance in plasma diagnostics with electromagnetic waves. A model for estimating total collision frequency of DC arc discharge plasma is built based on the Coulomb model and elastic scattering model. Explicit expressions for attenuation coefficient and transmission coefficient of THz wave propagating through a uniform plasma are obtained, which are expressed as a function of plasma frequency and collision frequency in the DC arc discharge. Detailed numerical analysis and discussions are conducted to reveal the influence of electron density, collision frequency, thickness of the plasma, and incident angle of the wave on the transmission characteristics of THz wave in plasma. Results show that the greater are the electron density, collision frequency and transmission length of a wave propagating in plasma, more power of the wave is attenuated. The attenuation energy of laser under horizontal sending and horizontal receiving (HH) polarity is as same as the vertical sending and vertical receiving (VV) polarity in underdense plasma.
Accurate solution of oblique reference wave for tilt phase aberration correction in digital off-axis holography
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In any off-axis holographic experiments, it is generally difficult to accurately obtain plane reference wave angle so that tilt phase aberration (TPA) occurs in three-dimensional phase reconstruction for the object. In this paper, a novel approach to accurately determining the plane reference wave angle for phase reconstruction of the object in digital offaxis holography is described. The method ingeniously constructs a numerical reference plane (NRP) reflecting true tilt of the reconstructed object by randomly choosing three points from a local flat of the reconstructed object image, and establishes the relation between NRP tilt and plane reference wave angle. So the reference wave angle can be exactly obtained by iterative computation and TPA is completely compensated. The experimental result approves of theoretical prediction very well.
Two distortion correcting methods for fisheye images
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Fisheye lens forms a circular image on the image plane which is different from people’s perspective view. This paper introduces two practical methods to correct the fisheye image from distortion. Distorted images can be corrected to the perspective views which are suitable for people to watch by rectilinear projection based on lens functions. This paper extended this method so that it can correct images taken by fisheye lens over 180°. Since the rectilinear projection method has the limitation that it can only correct a ROI, the second method based on an improved cylinder projection is proposed to overcome this limitation. The picture corrected by this method has less deformation compared with traditional cylinder projection method.
External calibration experiments of airborne millimeter-wave cloud radar using corner reflectors
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On April 2016 19-24, a calibration experiment based on corner reflector was carried out in field test zipengshan in Feixi County of Hefei city. The experiment had accomplished the calibration of airborne millimeterwave cloud radar under the condition of static ground. According to calibration data, the root mean square error of corner reflector strength measurement values between the reflector and the theoretical value is 0.182dB and 0.197dB in standard mode (pulse width is 0.33 s) and enhanced mode (pulse width is 1.32 s) respectively. All these pave the way for the further study of the external calibration experiments under the condition of clear sky sea.
A method for remote sensing image restoration using gyroscope sensor
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Fast image restoration for blurred remote sensing image is one of the focus problem in optical image processing. We present a method for remote sensing image restoration using a gyroscope sensor mounted with the camera. With motion track of the camera obtained from gyroscope sensor, we get a better PSF(Point Spread Function) estimation by calibrating the camera. Then we use the TV regularization to solve this non-blind deconvolution which runs faster than blind deconvolution. In experiments, we established a platform to simulate the vibration of satellite and get the synchronized gyroscope data in the exposure time, then we compare our restoration results with ground truth. Our experiments show that, the method has a good performance for blurred image caused by vibration of image system.
A robust evaluation method for motion distortion of TDICCD image
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In the process of remote sensing imaging, the obtained TDICCD images are always accompanied by distortion due to relative motion between imaging platform and the target. Traditional image evaluation metrics like Structural Similarity Index Measurement (SSIM) or Peak Signal to Noise Ratio (PSNR) are general assessments of image quality, but do not clearly evaluate distortion level. Considering the special properties of TDICCD images, this paper proposes a robust evaluation method to quantitatively describe motion distortion. The proposed method contains mainly three steps: image line PSF estimation, calculation of PSF deviation and overall computation of motion distortion. Numerical experiments have been done to simulate TDICCD motion distortion images under different vibration conditions whose results are later evaluated by the proposed method. Results prove that our method provides precise and robust quantitative assessment for images of different degrees of motion distortion.
Design of imaging circuitry of space CCD camera based on FPGA
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A imaging system of area-array CCD cameras based on FPGA was designed. The overall structure and design of the system was introduced in detail. According to the working mode and driving timing requirements of this CCD image sensor, the driving schedule under the control of FPGA was designed. The working mode and parameters of such an imaging system were aligned with the control signals in accordance with the general requirements of space CCD cameras. With FPGA device as the platform of hardware design, the hardware of integrated timing and control system was described in VHDL language. The A/D converter AD9945 based on the correlated double sampling was used to realize the analog-digital (A/D) conversion of ICX285AL output signals. The XQR2V3000-4CG717V developed by Xilinx was chosen to accomplish the design of this hardware circuit. Through simulation, the correctness of driving schedule was verified, thus preparing necessary hardware for the final development of space area-array CCD cameras with high performance.
Infrared image simulation for dynamic decoy
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From image processing angle, the research on the infrared characteristics of burning decoy based on sets of measured infrared images is developed. After that, the infrared imaging model of the decoy is constructed. At last the lifetime infrared images of decoy are generated. In order to achieve the above objectives, firstly, an accurate segmentation and extraction for burning area, radiation area and burning trail of decoy is accomplished; secondly, the infrared imaging model of the decoy based on lifetime, size and gray of each part of the decoy is constructed; lastly, the infrared images of decoy are simulated by combination of billboard texture mapping technology and particle modeling. This paper provides the method combining Billboard and particle system with the trajectory of nodes, the system can enhance the precision of characteristics simulation and motion simulation for the infrared decoy, thus increase the real-time ability.
Enhancing uniform intensity distribution in 4D light field data of plenoptic camera
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Plenoptic camera can sample object in the way of 4D light fields in a single snapshot, which is different from conventional camera. Vignetting in the plenoptic camera will result in non-uniform intensity distribution of 4D light field data. We propose a method in this paper to address this problem according to exposure fusion and patch-match. The uniform intensity distribution of 4D light field data can be enhanced by our approach. This work can be treated as a preprocess step for further application on 4D light field data. As more details are kept, the quality of depth estimation and digital refocusing with 4D light field data is increased by our method compared with previous method.
SURE-based optimization of image restoration for optical sensing
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Recently, ℓ1-based image deconvolution has demonstrated superior restoration performance to other regularizers, and thus, receives considerable attention. However, the restoration quality is generally sensitive to the selection of regularization parameter. The key contribution of this paper is to develop a novel data-driven scheme to optimize regularization parameter, such that the resultant restored image achieves minimum mean squared error (MSE). First, we develop Stein's unbiased risk estimate (SURE)--an unbiased estimate of MSE--for image degradation model. Then, we propose a recursive evaluation of SURE for the basic iterative shrinkage/thresholding (IST), which enables us to find the optimal value of regularization parameter by global search. The numerical experiments show that the proposed SURE-based optimization leads to nearly optimal deconvolution performance in terms of peak signal-to-noise ratio (PSNR).
Performance analysis of multi-Gaussian beams steered by rotational Risley-prism-array
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Rotational Risley-prism-array system is an effective way to realize high power and high beam quality of deflecting laser output. In order to reveal the quality performance of deflecting beam, the beam compression in the direction of deflection and far field energy centrality of a hexagonal-distributed 7-Gaussian beam array based on rotational Risley-prism-array were studied in detail in this paper. The analytic formulae of the pointing position for the outgoing beam based on the prisms’ rotational angles are calculated by using nonparaxial ray tracing method. Then, the analytical expression for intensity propagation was derived based on the extended Huygens-Fresnel principle. From the irradiance distribution and PIB curve in the focal plane, the quantitatively simulation shows that the beam compression will be more significant as the deflecting angle of emergent increases. The energy centrality will decrease as the propagation distance increases, the fill factor decreases and the deviation angle increases. The mathematical model and calculation results can offer a reference for optical engineering application.
Classification and quality evaluation of ginned cotton based on color image fusion technique
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Ginned cotton’s quality is one significant factor to evaluate the cotton grade and influence the yarn qualities. Ginned cotton is always mixed with contaminants during picking, storing, drying, transporting, purchasing, and processing. Manual evaluation is time consuming, labor intensive, and unreliable. This paper proposed a fast feature extraction algorithm is presented for the measurement of cotton defects in ginned cotton within a complex background. The edge of cotton defects are extracted from fusion of three channel image of color image. A criterion based on areas is proposed to achieve fast morphological analysis. The different defects can be inspected automatically based on different thresholds. The comparison experiments between measuring system and technician were done and analyzed. The costing time of measuring system was less than 30 seconds, and accuracy was 89.5%. The measuring results show the method can meet with the requirement of grade determination of ginned cottons.
Study on train wheel tread detects detection and classification
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Train wheel tread will produce scrapes, peelings and other defects due to the friction between wheel and rail surface for its long-running process. Tread defects not only have a bad affect for the stability and security of the operation of the vehicle, but reduce the service life of the bearing and rail facilities and do harm for the safety and efficiency of rail transport. Among them tread scrapes and peelings are the two main defects of train tread. In order to achieve the detection and classification of tread scrapes and peelings, a method based on image processing and BP Neural Networks model was presented for detection and classification of scrapes and peelings in train wheel tread. First we preprocess the acquired images, and extract the defects. Next calculate four characteristic parameters including energy, entropy, moment of inertia and correlation, and eventually we calculate the mean and standard deviation of those characteristic parameters as the 8 texture parameters. Then we adopt principal component analysis method to turn 8 texture characteristic parameters of these two types of defects into three unrelated comprehensive variables. Finally by extracting and analysis the texture features of tread defects, the recognition correct rate reaches to 93.3%. The result shows that the method can meet the requirement of train wheel tread defects online-measurement.
Ocean color retrieval based on time-series data during a red tide
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In complex waters, it is still a challenge to develop ocean color retrieval methods with high accuracy. In this work, we improved an Empirical Orthogonal Function (EOF) method with Equal Dimension New Information (EDNI) to retrieve chlorophyll a concentration (CHL) and phytoplankton absorption coefficient (aph(675)). EDNI was introduced to trace the variations in time-series data. EOF, combined with EDNI, helped to catch input parameters. The data used in this work were collected by optical buoy during a whole red tide in the Zhujiang (Pearl) River Estuary in August 2007. The average absolute percentage difference (APD) of CHL was 29.6%, which was smaller than those from other empirical algorithms. The APD of aph (675) were 23.8%, which was better than those from QAA_v5. In addition, we compared the results with those without EDNI, and found that the APDs of CHL and aph (675) without EDNI increased by about 20%.
The application of image super-resolution reconstruction based on compressed sensing in the intelligent mobile terminal
Zhenmin Zhu,
Fei Teng,
Haolin Sun,
et al.
Show abstract
The image super-resolution technology has a wide range of applications and development prospects due to hardware limitation and various kinds of degradations of the digital imaging system. However, it is a difficult problem to share and promote it based on the rapid development of web technology. In this paper, we proposed a scheme to apply the technology of image super-resolution in intelligent mobile terminal by sharing way. Firstly, the algorithm of single image super-resolution reconstruction based on Compressed Sensing is proposed and deployed to the Cloud Host in the server terminal. Then, the service background is built by using the thinkPHP framework and the site operation environment is constructed combined with the XAMPP toolkit, so the algorithm can be called and run by the script files of batch processing. Correspondingly, in intelligent mobile terminal, the preprocess image can be uploaded asynchronously to the Apache Server of the Cloud Host through designing the plugin by HTML5. In addition, the plugin of the Boostrap is used and the concept of Responsive Web Design is utilized subsequently, so the mobile terminal has good interactivity. Finally, image super-resolution can be done by interrupt request, and the result can be obtained dynamically in intelligent mobile terminal. Experimental results indicate that this scheme makes it possible to apply the latest theory in mobile terminal, which is feasible to solve the problem of poor quality of image in the field of engineering where the imaging process is not ideal.
SOPC-based real-time spots detection and ordering for an artificial compound eye of 3D object detection
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A real-time image capture and processing system for the artificial compound eye of 3D object detection is presented. A light spot in 3D space could be imaged as a series of spots on the image sensor by the compound eye we developed. In order to alleviate the pressure on data transmission, processing and storage, image processing algorithms including medium filtering, single-pass connected components labelling (CCL) and center of gravity (COG) were integrated into the camera. The camera was mainly made up with a single cyclone IV FPGA chip and it is a SOPC based system. The image processing algorithms were implemented as an intellectual property (IP) core that is applicable to the Avalon Memory-Mapped (Avalon-MM) interfaces. Then the output of the camera is a series of spot coordinates which is in a sequential order. From the results of testing, the maximum image processing rate is about 20fps, which has exceeded the maximum frame rate (15fps) of the image sensor at a high image resolution of 2048 × 2048.
Polarization characteristics of the paint plate based on single reflection
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The spectral reflectivity of the artificial target and natural background is similar, but the polarization characteristic is very different. In this paper, based on single reflection theory, the Mueller matrix model of single reflection is derived, and then the Mueller matrix measurement experiment of paint plates is carried out. The experimental results show that, different with natural backgrounds, the single reflection characteristics of artificial camouflage targets are obvious. Especially with small incident angle or small roughness, single reflection features of paints are more distinct, and depolarization ability is weak.
A compact finger-vein identification system based on infrared imaging
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Finger-vein identification has become the most popular biometric identify methods. The investigation on the identification algorithms always is the key point in this field. So far, there are many applicable algorithms have been developed. However, there are still some problems in practice, such as the variance of the finger position which may lead to the image distortion and shifting; during the identification process, some matching parameters determined according to experience may also reduce the adaptability of algorithm. Focus on above mentioned problems, this paper proposes an improved finger-vein identification algorithm based on template matching. In order to enhance the robustness of the algorithm for the image distortion, the least squares error method is adopted to correct the oblique finger. During the feature extraction, local adaptive threshold method is adopted. As regard as the matching scores, we optimized the translation preferences as well as matching distance between the input images and register images on the basis of Naoto Miura algorithm. Experimental results indicate that the proposed method can improve the robustness effectively under the finger shifting and rotation conditions.
Measurement of temporal and spatial distribution of smoke concentration field based on image processing
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In order to solve the problem of overall measurement of smoke mass concentration field and real-time dynamic measurement, a set of method is designed, which by collecting gray scale information of smoke distribution image, and then calculating the smoke mass concentration. The experimental results show that, under a certain environmental condition, the gray scale of smoke image has a strongly related quadratic linear relationship with the laser backscatter echo voltage at the corresponding position. Moreover, combining the relationship between the laser backscatter echo voltage and the mass concentration of smoke in the same position, the mass concentration of smoke can be calculated by the value of gray scale. The method of the paper refer to, breaks through the limitation of the existing equipment which only can measure the partial mass concentration of smoke, and the method provides a basis for the development of smoke real-time dynamic measurement of smoke.
Stray light correction of array spectroradiometer in ultraviolet band using lasers and filters
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Stray light due to the array spectroradiometer characteristic can’t be ignored in the ultraviolet region. In order to obtain a true spectral power distribution, stray light correction must be considered. Array spectraradiometer covering 200nm- 460nm is investigated using lasers and filters. First, several lasers are measured using the array spectroradiometer. Due to the fact that the wavelengths of the lasers are beyond the capabilities of the spectroradiometer, the response in the UV region is originated from stray light. Results show that the stray light contribution is at the level around 2×10-5. In order to correct the stray light, filters with different bandpass wavelength are used to correct the stray light from different wavelength region. Results show stray light consistency using lasers and filters.
Study on image quality assessment under foggy condition
Xiangfeng Xue,
Hui Yang,
Song Xue,
et al.
Show abstract
Image quality assessment can provide important prior knowledge for subsequent picture processing, but it may be challenged by foggy distortion under a foggy weather condition, and there is no effective solution for the distorted images. In this paper, an effective image quality assessment method under foggy condition was proposed, with the purpose of giving image quality scores and their changes under different foggy density. Based on 29 reference images in LIVE image database, different image samples in a foggy day were generated. On the basis of analyzing foggy influences on image quality, this paper extracted features representing image scene characteristics in foggy day, used a method based on codebook to encode features, and trained features after using pooling strategy to encode, and, finally acquired image quality scores through the regression mode. Experimental results showed that, the higher accuracy, subjective and objective consistency, and higher identification on image quality under different foggy density can be obtained by the codebook-based method rather than other normal algorithms. The algorithm in this paper can solve the problem of image quality assessment under foggy condition.
Underwater linear object detection based on optical imaging
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Nowadays, more and more underwater electricity or communication cables and oil or gas pipelines have been installing. Equipment aging and damages to them have caused series of accidents, resulting in huge economic loss and environmental pollution. This paper proposes a long distance underwater linear object detection method based on range-gated optical imaging, which can help the maintenance and inspections of underwater cables and pipelines. The whole object detection algorithm can be divided into three stages: image enhancement, edge detection and object detection. In the image enhancement step, The system deals with the low contrast, blur and noises characteristics of underwater images by means of contrast normalization, median filtering, wavelet transform, and finally gets high quality images. Then, the Canny operator was used to extract object's edge features. Finally, for the emergence of noise edges, a robust algorithm named Random Sample Consensus was chosen to accurately detect linear object and estimate its parameters such as position and direction. This algorithm has been tested on the experimental data in the boat tank of Huazhong University of Science and Technology, collected with a range-gated imaging system. The results show that the algorithm can effectively detect underwater curved-linear objects, with the detection rate achieving 96%, and the effective detection range can be up to 5 times the length of the underwater decay.
Characteristic research on terahertz radar: cross-section measurement and imaging
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At present, the mechanism and devices of terahertz radar detection and imaging has attracted a lot of interest. Based on 4-f terahertz time-domain spectroscopy (THz-TDS) technology, a broad-band time domain terahertz radar system (0.1- 1.3 THz) was built for scattering and imaging characteristics of objects. Far-field radar cross-section measurements of different metal scaled models at terahertz frequencies were performed. The novel broadband radar can provide RCS distributions at arbitrary frequency and frequency-averaged RCS. Moreover, based on improved filtered back projection algorithm, imaging of the scaled models has also been retrieved, which can be helpful for scattering points searching and military shape optimization.
The application of wavelet transform in processing the signal of solar spectrograph
Sheng Huang,
Si-long Zhang,
Zai-hong Hou
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The solar spectrograph firstly takes the real-time accurate tracking of sun, then detects all monochromatic light within a certain wavelength simultaneously by making use of grating splitter, and finally obtains the continuous atmospheric parameter with high precision. In order to improve the accuracy of data and simplify the structure of the optical system, this article introduces the application of wavelet transform in removing noise and correcting baseline for the data measured. Baseline wander is mainly concentrated in the wavelet coefficients of low frequency band, while useful spectrum signal usually distributes in the wavelet coefficients of high frequency, and baseline wander can be removed by setting approximation coefficients to zero. Because of the time-frequency locality of wavelet transform, on the same frequency band of wavelet domain, the peak of the spectrum is compressed in few time channels. As a result, the amplitude of corresponding wavelet coefficients is bigger; On the contrary, the wavelet coefficients of noise is distributed on all the time channels with smaller amplitude of wavelet coefficients, so that the threshold method is used in this article to remove noise. The experiment shows that it is more suitable to decompose the spectrum signal at level 15 on the wavelet basis of sym5 with the approximation coefficients being set to zero and to process the detail coefficients by adaptive hard threshold. Examples show that this method provides an effective way to remove noise and correct baseline in the solar spectrum.
Polarization image enhancement based on depth image segmentation in haze weather
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An image enhancement method for polarized images in hazy weather based on the segmentation of depth image is proposed in this paper. Using the depth information which produced by the polarization-based restoration algorithm for haze-degenerated images, we segment the polarized images, and apply local histogram modification according to the result of the segmentation. The test results show that the algorithm can effectively improve the contrast of the distant target.
Target tracking of structure algorithm based on skeleton and corner for extended objects
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Due to extended objects are influenced by occluded and blurred edge, the stability of target tracking is not good by the figure algorithms or the corner algorithms. In order to solute this problem, an improved multi-resolution(MR) fuzzy clustering algorithm based on Markov random field(MRF) is firstly used to segment the candidate targets of the extended objects from the observed images, then a new proposed target tracking structure algorithm, based on the stabilization of the extended objects’ skeletons and the partially un-occluded and un-blurred edge feature of the extended objects, is applied to extract the skeletons, corners, intersection points and their spatial location relationship of the candidate extended targets to determine the true tracking target or not. The experimental results show that the established algorithm can effectively complete the segmentation and extraction of the partially occluded and blurred extended objects with a very satisfied reliability and robustness.
Fast image haze-removal algorithm based on mixed filter
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According to the theory of dark channel prior a image haze-removal algorithm is proposed in this paper. The algorithm uses maximum-minimum value filter combined together with guided filter to remove haze from the original image and uses wavelet to enhance the visual effect of the de-hazed image. Using maximum-minimum value filter only can cause the problem that the algorithm depending on the value of transmission lower limit excessively, by using maximum-minimum value filter combined together with guided filter the problem can be solved efficiently and the transmission matrix is refined adaptively. The white halos and patchy singularities which exist at the edge of the depth field in the reconstructed image is eliminated. Furthermore the algorithm refine the values of transmission which are estimated too big or too small. Finally wavelet is adopted to enhance the visual effect of the de-hazed image effectively. The objective evaluations of the reconstructed de-hazed image such as reconstructed image entropy, reconstructed image variance, reconstructed image mean square error, the degree of reconstructed image change and reconstructed image clarity are also studied in the paper, but these indicators can not represent the advantages and disadvantages of the performance of the image haze-removal algorithm, so it still needs further study in this field.
The application of GPS positioning accuracy optimization algorithm based on support vector machine (SVM) theory in atmospheric remote sensing
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Atmospheric coherence length monitor realizes continuous observation of the star for all-weather, and it is a kind of conventional instrument to measure the coherence of the atmosphere. In the actual measurement process, the atmospheric coherence length meter instrument needs through the GPS receiver to locate the local longitude, latitude and GPS time, in order to calculate the star position in real time. When the signal conditions are not ideal, such as indoor, forest and urban environment, the phenomenon like occlusion, multipath and interference are more severe. At this point, will lead to signals of GPS receiver appear error and the GPS receiver positioning accuracy will be greatly reduced, May lead to the telescope cannot tracking stars normally. In order to improve the GPS receiver positioning accuracy, the support vector machine (SVM) theory based on statistical principle is adopted to avoid the "overfitting problem" which minimizes the risk of simple experience. Application of GPS receiver receives the data information in different environment as the training sample and test sample, Data information include longitude, latitude, and satellite elevation, satellite azimuth, and satellite signal-to-noise ratio, which may affect the accuracy of GPS positioning. Using the linearly separable support vector machine (SVM) algorithm, by finding out the maximized class distance to get the optimal classification super planar to classify the data sets. And then, enter the stage of testing, according to the positioning accuracy classification results, predict the future output data, filter the positioning accuracy of the error data.
Control of the focal depth by annular phase-only pupil filters
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The general scalar diffractive theory for Gaussian beam has been investigated. The two-zone and three-zone annular phase-only pupil filters are adopted to provide specific numerical descriptions of improvement of DOF, respectively. The simulated results show that the annular phase-only pupil filters can be used to control the DOF of the optical system. For the well designed filters they can help improve the DOF in the axial direction and increase the resolution in the transverse direction, simultaneously. However, the Strehl ratio of the optical system maybe decline and the side-lobe to peak intensity ratio will increase with the improvement of the DOF which is hard for the optical imaging. Comparison results show that the two kinds of three-zone annular phase-only pupils have the same impact on the control of the light intensity distribution.
Hand vein image enhancement based on phase congruency
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It is necessary to improve the quality of the captured hand vein image in the vein display device and vein recognition system. In this paper, a method of hand vein image enhancement based on phase congruency is proposed according to the structure and features of human hand vein images. Firstly, multiple images containing vein edges are acquired by applying phase congruency which parameters are set differently, and two images that contain the majority of vein and less noise are selected by image entropy values, then the chosen images will be enhanced by contrast enhancement. Finally, the original image and the enhanced image will be fused in gradient domain. The experiment results show that the proposed algorithm can enhance the contrast of the hand vein images efficiently, improve the quality of image significantly, and suppress noise perfectly.
Calculation of atmospheric attenuation at 90~100GHz
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Factors of atmosphere was taken into account for the attenuation coefficient calculation. Atmospheric attenuation of whole atmosphere was given. The result contrast was done between ours and literature. And they fit well.
Convolutional neural networks based on sparse coding for human postures recognition
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This paper presents a convolutional neural networks (CNN) based on sparse coding for human postures recognition. It’s an unsupervised approach for color multi-channel processing. The improvement of the method is mainly reflected in two aspects. We transform sample images into patches and make a decorrelation between input patches and reconstructed patches. In addition, we use the convolution kernels extracted by sparse coding to replace the initialization of the convolution kernels for human postures recognition. The proposed method is tested in the public KTH pedestrian behavior dataset and HUMAN-V2 self-test dataset. Compared with the traditional way, our approach shortens the training time a lot and also improves the recognition rate. Our experimental results verifies the effectiveness.
Image quality improvement in optical diffraction tomography by multiple numerical propagations and separated reconstructions
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The image quality of optical diffraction tomography is likely to decline due to some key factors, including limited depth of focus, the rotational error and localized RI discontinuities. This paper describes reconstruction methods to circumvent these three factors for improved image quality. The limited depth of focus and the rotational error are addressed simultaneously with a method based on multiple numerical propagations. The localized RI discontinuities are addressed with a method based on separated tomographic reconstructions. Experimental results are demonstrated to verify the described methods. A four-core optical fiber and a large-mode photonic crystal fiber is measured and processed by the method based on multiple numerical propagations with improved image quality. The depth of field is significantly extended. Samples with different typical RI discontinuities, two kinds of fusion spliced optical fibers, are measured and reconstructed. While reconstructions by existing methods are heavily disturbed, the 3D maps obtained with the described method are free from spreading disturbance and show important structures as well as the positions and estimated shapes of the discontinuities. The described methods are of practical significance and will find important applications in 3D imaging of various objects.
Resolution-improved Fourier ptychographic microscopy using high-numerical-aperture condenser
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High-resolution (HR) and wide field-of-view (FOV) microscopic imaging plays a central role in diverse applications such as high-throughput screening and digital pathology. However, for bright-field microscopy system, high-resolution and wide field-of-view (FOV) always could not be achieved simultaneously, limiting its applications which require large space-bandwidth-product (SBP). Various super-resolution techniques have been proposed to break this limitation, such as on-chip sub-pixel scanning methods, structured illumination microscopy, and Fourier ptychographic microscopy (FPM). Among these super-resolution techniques, FPM became increasingly popular recently since it can combine the numerical apertures (NAs) of the objective lens and the illumination light to form a larger synthetic system NA without sacrificing the FOV. Thus, the resolution-FOV tradeoff can be effectively decoupled in FPM. In addition, it is also very convenient to build an FPM system by simply replacing the illumination system of a bright-field microscope with a commercial programmable LED board. Lately, a lot of efforts have been made to improve the accuracy and efficiency of FPM, however, to date, the effective imaging NA achievable with a typical FPM system is still limited to the range of 0.4-0.7. Here, we build an FPM platform using an oil-immersion condenser to boost the resolution of a bright-field microscopy system and significantly increase its SBP. This FPM system involves a 10X 0.4NA objective lens and a 1.2NA oil-immersion condenser to synthesize a system NA of 1.6. We confirmed the accuracy of this technique by achieving a half-pitch resolution of 154 nm at a wavelength of 435 nm with a FOV of 2.34 mm2, corresponding to an SBP of 98.5 megapixels (~ 50 times higher than that of the conventional incoherent microscope with the same resolution). We also demonstrated the effectiveness of this approach by imaging various biological samples, such as human blood smears. Our work indicates that FPM is an attractive method which could broadly benefit wide-field imaging applications that demand large SBP, and it still has a great potential to achieve much larger SBP of bright-field microscopes.
A new image fusion and monitored control system based on Raspberry Pi and Yeelink platform
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Image fusion has been widely used in medical, computer vision and other fields. However, the traditional based on PC, FPGA and DSP image fusion system cannot satisfy requirements of portable, low power consumption and low cost.Raspberry Pi is a new type of microcomputer based on ARM, compared with traditional image fusion system, Raspberry Pi volume, price and power consumption is very low. With Raspberry Pi as core, and special camera of Raspberry Pi, router, PC, mouse, keyboard hardware, C++, OpenCV software, and Yeelink cloud platform build innovative image fusion system is able to meet small volume, low power and price requirements. Yeelink is a new type of Internet of things, providing access to sensor data, storage and display services. The terminal user can observe required information in real time through local area network. NonSubsampledContourlet Transform (NSCT) with multi-scale, multi-direction, multi-resolution and good shift invariance. Because of down sampling, traditional Contourlet transform will cause Gibbs phenomenon, NSCT can overcome the disadvantage, obtaining better fusion image. This paper makes full use of characteristic of Raspberry Pi and Yeelink, construct a new image fusion and scene monitoring system, images is processed by Wavelet, Contourlet and NSCT algorithms, finally analysis the results. The new system has great research and application value.
Fluorescence instrument based on direct view holographic grating prism for remote sensing
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We present an optical receiving system for LIF lidar using a direct view spectrometer based on holographic grating prism. The proposed receiving optical system consists of receiving telescope, slit, collimating lens, holographic grating prism, objective lens and ICCD camera. The receiving optical system based on this dispersion structure can not only reduces the optical distortion to offer a high optical efficiency, but also has a more compact structure which is very suitable for spectral dispersion of remote target. The system adopted an intensifier coupled a CCD to make up an ICCD camera. Based on real-time background subtraction algorithm, 60fps fluorescence spectrum can be obtained in real time. System validation experiment uses a semiconductor laser as excitation source to illuminate oil target to radiate fluorescence at a distance of 30 m. The fluorescent signal is received by the set up LIF lidar receiving optical system, and clear spectrum image is obtained. The designed in-line, direct view configuration holographic grating prism spectrometer owns the advantages of high light throughput, less optical distortions, compact structure, small volume and easy operation, which make a practical portable receiving optical system.
SMT stencil automatic registration based on MBR
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An automatic registration method for Surface Mount Technology (SMT) stencil image is proposed. During the registration, the minimum bounding rectangle(MBR) of the Stencil changes with the stencil’s arbitrary placement and angle, while the absolute minimum distance between the registration feature point and the rectangle vertex remains unchanged. This character can be used to solve the random error and failure rate in stencil placement. With three feature points in standard Gerber data image and in stencil image, the affine transformation is carried out. After mapping the coordinate systems of the Gerber image and the stencil image are consistent with each other. Then the internal automatic matching test and secondary registration are introduced to improve the accuracy. The results of experiment show that this method can significantly improve the efficiency and intelligence level of SMT.
Simulation and analysis of laser beam adaptive focusing using an extended uncooperative target in the loop
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A conventional adaptive optics system utilizing a beacon light on or near the target for wavefront sensing is often used to compensate the phase aberrations of laser beam propagating through optically inhomogeneous media. However, there is no such a spatially coherent emitter could be used in most cases, one must rely on the reflection or scattering light from an uncooperative extended target itself to probe the atmosphere channel. In this paper, we show that an incoherent target return could be utilized to adaptively focus a collimated laser beam onto a rough target through atmospheric turbulence by simulation. A laser transmitting and receiver system combined with a wavefront sensorless adaptive optics system based on the modified stochastic parallel gradient descent (SPGD) algorithm simulation platform is established. The results show that all the maximum intensities among 1000 simulations increased and a single localized region of high intensity was achieved 78.7%. Additionally, we verified the system performance at different turbulent strength and discuss these limitations.
Real-time haze removal by GPU acceleration based on dark channel prior algorithm
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Dark channel prior haze removal algorithm is very simple and effective for single image haze removal, but it’s somehow limited by color distortion in gray areas and expenditure of time. Firstly, aiming at solving color distortions, we propose a modified dark channel prior haze removal algorithm. We correct the transmission of the gray areas by introducing the correction parameter, and the transmission is unchanged when the areas meet the law of dark channel prior. Secondly, to realize real-time haze removal for video surveillance, we use GPU to parallel accelerate and optimize the new algorithm on Compute Unified Device Architecture platform released by NVIDIA. Experiments show that the modified algorithm works effectively in gray areas. At the same time, the processing speed of images with a resolution of 640x480 can reach 37 frames per second after GPU acceleration and can also obtain the real-time haze removal result.
BP neural network used in recognition algorithm for star pattern
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Star identification algorithm is the key of posture measurement for star sensor. In order to solve the problems of low identification speed and poor robustness, this paper presents a new method which is based on the star identification algorithm of the BP neural network by referring to the idea of Grid algorithm. The grid algorithm can divide a star map into a grid, which can be transformed into a matrix. In this paper, the method of meshing is improved so that the newly generated matrix is the input sample. About the output sample, each star will be numbered and each number represents a star. So the output sample can be represented by the number in binary system. The classifier uses K-MEANS algorithm to achieve clustering of unsupervised similar samples. Finally, the simulation experimental results show that the success rate of the method is ninety-nine percent and recognition speed is greatly improved. After adding a variety of noise tests, there is still a high recognition rate. The method in this paper can improve the recognition speed and robustness.
A multispectral target tracking algorithm based on particle filter
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Target detection and tracking important in many applications including intelligent monitoring system, defense system and terminal guidance system. Aiming to solve the problem of simulated target tracking, this paper proposes an adaptive algorithm which uses the fusion of the spectral and morphological features of multispectral image to realize the target tracking based on the Particle Filter. Firstly, the target area is manually initialized in the multispectral image and the spectral and texture features of the target are extracted. Secondly, we build the adaptive tracking model of multiple features under the framework of Particle Filter. We validate the effectiveness of the proposed approach on the MATLAB platform. The results show that the proposed approach achieves accurate and stable multispectral target tracking in complex scenes by improving the efficiency of particles usage under defective tracking conditions, which is of great theoretical and practical values for the application of multispectral target tracking technology.
Method of student identification through college classroom surveillance videos using deep learning features and label propagation
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For education or management, it is often necessary to identify students with their identification (ID) photos through the surveillance videos of the college classrooms. This is a typical application of ID photo based single-sample per-person (SSPP-ID) face recognition. After analyzing the main challenges, we propose a framework by combining deep learning method and label propagation algorithm together. It is composed of three sequential steps: the first step aims to partition the face image into several patches and get an unbalanced-patch based feature using ConvNets; In the second step, we select a few key-frames by using the log-likelihood ratio calculated by the Joint Bayesian model; The last step uses label propagation algorithm to propagate the labels from the key frames to the whole video by simultaneously incorporating constraints in temporal and feature spaces. The performance of the proposed method is evaluated on Movie Trailer Face Dataset and practical college class surveillance videos. Experiments with these challenging datasets validate the utility of the proposed method.
Infrared dim and small target background suppression based on improved anisotropy filtering
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Infrared small target is easy submerged in the complex background, to improve the ability of detecting target, which by inhibiting the background to enhance the target signal. Focusing on the shortcomings of the isotropic background prediction method, a kind of improved anisotropic infrared background prediction method (IABP) is proposed. According to differences of local gradient character among target region, smooth background region and undulate background region, the edge stopping function of anisotropic partial differential equation is improved. Then the mean of the two least values of the edge as the prediction value of the background. Finally in order to extract the candidate target and reduce the false alarm rate of the real target, which the difference between the background image and the original image is processed. Experimental results show that: 1) improved anisotropy of background prediction for different scenes can obtain good background prediction effect; 2) improved anisotropic background predication for the signal-noise ratio (SNR) was lower than 2.3db could be loyal to the true background of the original image to the maximum extent, presenting a superior overall performance to other background prediction methods.
Analysis of laser intensity attenuation and compensation and the influence on imaging through particle field
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In 3D particle image velocimetry (PIV), when laser transports through dense trace particle field, scattering light intensity vary in different directions. In this article, we build 5 fields of different densities, and each field contains one vortex ring. The diameter of the vortex ring is 2mm, and the particles are dense in the ring and sparse outside the ring. Based on the Mie scattering theory and Monte Carlo method, we compute the laser intensity difference along the direction of incident light in each particle volume when the laser beam transports through it, and obtain the relationship of laser intensity, particle density and the distance of laser transportation. The variation of laser intensity could also be viewed from different directions. We also discussed the influence of light intensity variation on integrated imaging particle-imagevelocimetry (PIV) image’s quality in this paper. To deal with this variation, we propose a new light intensity equalized compensation method. By using this method, we can reduce the influence of attenuation when laser light transports through dense particle areas. During the simulation process, a camera array is set to detect the forward and back direction of the laser beam in the region, and the light intensity is recorded by different pixels. Light intensity attenuation of different positions is considered. All cameras are treated as pinhole models. The results show that front scattering and back scattering have great effects on integrated imaging PIV. The compensation method is used in experiment to preprocess particle images.
Accurate camera calibration with color phase-shifting wedge grating arrays
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In order to reduce human interaction and the workload, a method using a color phase-shifting wedge grating array is proposed for accurate camera calibration, which needs only one frame at each pose. Firstly, the zero-phase points are roughly extracted by edge detection algorithm and optimized by windowed bicubic fitting with sub-pixel accuracy. Secondly, a simple linear fitting algorithm is used to obtain zero-phase lines and acquiring their intersection points. Finally, the intersection points coinciding with circle-centers are regarded as feature points to calibrate the camera. The effectiveness and accuracy of the method is verified by experiments with real images even under color-coupling. It is shown that our method is accurate and reliable comparing with the checkerboard.
Design of multi band laser echo detection system
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Laser echo has an important application in target detection and identification, beam quality analysis and so on. In the paper, a receiver for detecting laser echo signal is designed. Combined with the far field target plate, the facula performance test of photoelectric products can be carried out at the outfield experimental station. The laser echo receiving device mainly includes optical system, photoelectric conversion module, signal processing system, data processing and display control system and so on. The optical focal length of receiver is 1299.99mm, caliber 160mm, and image resolution is 320*256. Finally, the correctness of the laser echo receiver is verified by simulation experiments.
Immune particle filter algorithm for target tracking based on histograms of color and oriented gradient
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Focusing on fails to track with standard particle filters when object and background have similar color and object is occluded, a new algorithm of immune particle filter object tracking based on histograms of color and oriented gradient is proposed. Color histogram is the global description of targets in color image, histogram of oriented gradient contains some construction information. The gradient feature is added, the poor performance of only one feature is improved when the environment changes. In addition, the proposed immune optimization algorithm improved the diversity of particles, especially the decline of the impact of sample impoverishment when occlusion occurs. Experimental results show that the proposed method is able to track the object stably, when one of the features loses discrimination ability for tracking. It is simple and suitable to be applied to deal with tracking problems in complex scene.
Adaptive learning rate method based on Nesterov accelerated gradient
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A kind of stochastic gradient descent method of self-adaptive learning rate is proposed in this thesis. This method is based on the optimization algorithm Nesterov accelerated gradient (NAG). First second derivative approximation of cost function is executed, then the final update orientation is corrected through self-adaptive learning rate, and the convergence of the method is analyzed theoretically. This method required no manual adjustment of the learning rate and is robust in the selection of noise gradient information and hyper-parameters, featuring high computation efficiency and small memory overhead. Finally, a comparison is made between this method and other stochastic gradient descent methods through MNIST digital classification task, and the experiment result showed that Adan worked well with the faster rate of convergence and is better than other stochastic gradient descent optimization methods.
Noise properties of the calculated linear polarization image
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A method of calculating the 1D polarimeter imaging results from 3D polarimeter intensity measurements is introduced, and the influence of the detector noise on the calculated results is studied. Noise analysis is mainly carried out for the commonly used Pickering imaging method, Fessenkovs imaging method and modified Pickering imaging method with additive noise and shot noise as real noise sources. The analysis and simulation results show that, if the analyzer angles are evenly distributed over the half-circle, the additive noise variance of the calculated image is only related to the channel number N of the polarization imaging system, and the shot noise variance of the calculated image is related to the Stokes vector, the calculated angle, the channel number N and the polarization imaging modality. If the analyzer angles are not evenly distributed over the half-circle, concrete analysis should be made according to concrete circumstance. On the whole, the modified Pickering method is a recommended imaging modality by reason of it can suppress the noise of the calculated image because it has more channel numbers and it is not affected by the incident Stokes vector or the calculated angle.
Realization of measurement method in angle intersection based on MATLAB
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Accuracy Measurement on aerial track of moving target is one of the major target for photoelectric theodolite, which target is solved by angle intersection algorithm of two-stations. For analyzing the accuracy and the photoelectric theodolite of the angle intersection measurement, this paper simulated 6 aerocrafts’ tracks. L,K algorithms of coplanar rendezvous and MLE algorithms of non-uniplanar intersection were used to measure aerocrafts’ tracks. The measurement result was relative analyzed with simulation track in angle intersection, then the L,K ,MLE algorithm’s applicability was fixed. One aerocraft track of simulation was chosen to measure by MLE algorithm in different station-setting conditions. The measurement error was compared in intersection angle, azimuth angle, pitching angle, baseline length, station location. And the relation between the conditions and measurement accuracy of tracks was fixed. Also the condition of station-setting was fixed. The work above has directive significance in the intersection algorithm choice and station-setting later.
Measurement elements of optical equipment are teams of A, E, which is shorten as nAE. The nAE is belong to angle intersection measurement mechanism [1]. The optical equipment usually supplies angle information only, two-stations theodolites or n-station theodolites are used in solid intersection measurement, and spacial coordinate of aerocraft is fixed [2]. This method is called angle intersection measurement. This article simulated 4 aerocrafts tracks, and used 3 algorithms above to measure the tracks [3]. The measurement result was relative analyzed with simulation tracks in intersection angle, and the L, K, MLE algorithm’s applicability was fixed [4].
Usage of photoelectric theodolite faces the problem of station-setting, and the station-setting directly influences the measurement accuracy of track [5]. This article chooses one aerocraft track to measure by MLE algorithm in different condition of station-setting. The measurement error was relative analyzed in intersection angle, azimuth angle, pitching angle, baseline length and station location, by which the relation between measurement accuracy and 5 conditions was fixed. The condition of station-setting was fixed on the base.
An improved longitude-latitude mapping algorithm for fisheye image calibration
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Field of view (FOV) of the fisheye lens is close to or even higher than 180°, which brings about extraordinary imaging effect that the visual range would be far wider than the human eye perspective. However, the wide visual range of the fisheye lens is always at the expense of image quantity, so that the images obtained by fisheye lens would inevitably show a large degree of distortion aberration. In this paper, we propose an improved distortion calibration algorithm of longitude-latitude mapping to eliminate the image distortion aberration caused by fisheye lens. This method does not need to depend on a specific physical camera and has general and universal significance. By using Matlab as a mathematical analysis tool, the verified experiment and the corresponding write code is performed to correct a specific fisheye lens’ image based on the previously proposed algorithm. A reverse mapping is used to avoid cross-border problems, and comparative experiments are also analyzed to show the difference between the image processing with the traditional and the proposed algorithm. Experimental results demonstrate that the proposed algorithm can better achieve the correction of fisheye lens distortion. The twisted lines that are not expected can be well corrected into the straight lines. This method can not only reduce the problem of horizontal stretching of the image, but also make the processing results visually consistent with people's viewing habits.
Comparison of two types of color transfer algorithms in YUV and Lab color spaces
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For the purpose of coloring the night-vision images captured by low-light image intensifiers or infrared thermal imagers, color transfer algorithms were used to transfer natural colors to these gray images. Most of the color transfer algorithms can be divided into two classes: global color transfer and point color transfer. In global color transfer algorithms, the means and variances of the initial false color image were adjusted according to those of the reference color image. In point color transfer algorithms, the matching points were determined between the grayscale image and the reference color image. These two kinds of algorithms are always carried out in two common color spaces: YUV color space and Lab color space. The color space influences the performance of the color transfer algorithms. In this paper, several typical color transfer algorithms, including basic ones and multi-resolution ones, were carried out in different color spaces. The results show that global color transfer algorithms perform better in the YUV color space and the Lab space is more suitable for point color transfer algorithms. The biggest difference between these two color spaces is that the correlation between the channels of Lab space is much lower than that of YUV space. The global color transfer algorithms adjust the color components of the initial false color image with a uniform conversion, linear or non-linear ways. This process can benefit form the correlation between the channels, which is much higher in YUV space. However, the coloring process of the point color transfer algorithms is independent from the points matching process based on grayscale. This is the reason why the point color transfer algorithms should be implemented in the Lab space.
An improved phase diversity wavefront sensor based on the altered exposure time of camera
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Since the phase diversity (PD) wavefront sensor has the advantages of simple structure and high light energy utilization, it is one of most attractive wavefront detection tools. The accuracy of retrieval wavefront depends on the precision of the detective intensity distribution of the CCD camera. However, limited by manufacture craft, the noise data are inevitably recorded, so CCD has only good performance in fixed dynamic ranges. In this paper, we propose a simple modified phase diversity wavefront sensor based on the altered exposure time of camera to improve the dynamic ranges of CCD. The two images are taken under normal exposure time and saturated exposure time of CCD, and then they are stitched to form a perfect image including accurate high space frequency and low space frequency information. Under same signal to noise ratio a comparison between the improved phase diversity wavefront sensor and the traditional phase diversity wavefront sensor is made by using simulation. The results show that this method can significantly enhance the retrieval wavefront accuracy.
A sub-µW low temperature sensitivity CMOS RC oscillator
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Nowadays, portable imaging surveillance systems are widely used in military and civil fields. Such systems always need low power consumption to meet the requirements of long-term operation. These systems are in standby mode during most of the time and woken up at a regular interval for a very short time to perform a measurement. Accordingly, a low power oscillator as wake-up clock generator is needed. In this paper, a sub-μW low temperature sensitivity RC oscillator is presented. Unlike the traditional CMOS RC oscillator with double comparators, it contains only one hysteresis comparator and operates in subthreshold region to reduce current consumption. The oscillator has been designed and simulated in a standard 0.18 μm CMOS process, achieving a frequency of 100 kHz. The variation of frequency is ±1:65% over the temperature range from -10°C to 110°C. The current consumption is 332 nA under a supply voltage of 1.8 V at room temperature. The occupied area is merely 0.01 mm2 without pads.
An optical nano-antenna structure of metallic ball array for enhancement of near-infrared photodetection
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This work is aimed at designing an optical nano-antenna structure to enhance the optical absorption in 1.0−1.7 μm and improve the performance of InP-based InGaAs sensors. We report comprehensive analysis of an optical nano-antenna structure of metallic ball array for surface plasmon enhancement of near-infrared photodetection. The enhancement capability of metallic ball array on InP substrate with periodicity in the range of 600−1200 nm and diameters in the range 100−300nm has been studied by theoretical modeling with a finite-difference time-domain(FDTD) method. Our simulation results show that the highest transmission efficiency is achieved when the diameter of the ball is around and the optimized periodicity of the ball array is around 800nm. After comparing the transmission spectra of the arrays made of different metals, silver is found to be the best. Because of the speciality of SPP modes, the enhancement relative to wavelengths near 1.1μm is obviously weaker than that near longer wavelengths. Coating a SiO2 film about 500nm over the arrays is found to be an effective solution to achieve higher transmission efficiency around 1.1μm.
One-parameter l1 Prior in Variational Bayesian Super Resolution
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In this paper, we address the multiframe super resolution problem from a set of degraded, under-sampled, shifted and rotated low resolution images to obtain a high resolution image using the variational Bayesian methods. In the Bayesian framework a prior model on the high resolution image need to be specified, its aim is to summarize our knowledge of the image and to constraint the ill-posed image reconstruction problem. Appropriate prior model selection according to the super resolution scenario is a critical issue. Here we propose the one-parameter l1 prior. Experimental results demonstrate that the proposed method is very effective and compared favorably to state-of-the-art super resolution algorithms.
Automatic fall detection using optical flow and shape context from the panorama view
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As most countries are facing the growing population of seniors, automatic detection for abnormal behaviors has been a promising goal for a vision system operating in supportive home environment. In this paper, we investigate a novel approach for fall detection which is frequently observed in elderly people motions using a panorama camera mounting on the ceiling, we employ and modify a combination of two different features representing fall events: optical flow and human shape variation, which allows fall detection conducted from coarse to fine. In the pre-processing step, we analysis the raw video data to extract the meaningful motion region,then we designed an energy function as representing phase and magnitude of optical flow vector for the coarse detection in temporal domain, where the information entropy is adopted as the abnormal coefficient to estimate the consistency of motion directions. Once the optical flow changes abnormal, shape context descriptor is introduced to do the template matching for the fine detection, here we propose a novel shape matching descriptor which improves the rotation invariance based on the traditional shape context, while remaining its tolerance to most shape distortion. Our method is evaluated on a panorama-view fall detection database including fall events and confounding events, we demonstrate more effective performance and less computational costs on the fall detection regardless of challenging conditions and encourage the potential use of a vision-based system to provide safety and security in the homes of the elderly.
Centroid computing of far-field spots based on sub-aperture retro array
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Since the jitter frequency of incident laser beam becomes higher in the ‘Common Path/Common Mode’ (CP/CM) system due to the guiding system added to the laser module, the current laser-beam stabilizing control with hartmannshack sensor is not enough. As we all know, better beam stabilizing control effect requires higher detecting frequency. Generally, the detecting frequency of hartmann-shack sensor in the CP/CM system is far lower than the far-field spot. So we want to use the far-field spot of the SARA to feedback instead of the hartmann-shack sensor. In this work, we study the far-field spot of a 61-unit SARA from the CP/CM system. We ratiocinate the process of the simulation based on Fresnel diffraction and Fourier optics. Comparison between standard far-field spot and the far-field spot from sixty one units SARA based on duty ratio of the retro reflectors and different wavefront tilts aberrations is given, while the wavefront is given in zernike model.
Performance of InGaAs/InP planar infrared detector with different passivation films
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In order to study the effect of different passivation films on the detector performance, the front-illuminated planar-type 256×1 element InGaAs/InP detectors were fabricated with SiNx film and SiO2 film. The SiNx film was deposited by plasma enhanced chemical vapor deposition (PECVD) and SiO2 film was deposited by magnetron sputtering technology. The electrical properties and photoresponse characteristics were investigated after the detector mounted on dewar. The photoresponse maps from laser beam induced current (LBIC) method show that the isolation of adjacent elements of the detector with SiNx film is better than the detector with SiO2 film. Furthermore, at room temperature the average density of dark current and the average peak detectivity of the two kinds of detector is 26.8 nA/cm2 and 41.2 nA/cm2 at 100 mV reverse bias, 1.21×1012 cm·Hz1/2/W and 1.08×1012 cm·Hz1/2/W respectively. Therefore, the detector with SiNx film deposited by PECVD could availably passivate the surface in comparison with the detector with SiO2 film by magnetron sputtering technology.
Cloud motion measurement from satellite images using iterative multigrid image deformation approach
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The measurement of cloud motion is very useful in weather forecast and natural disaster management. This paper is focus on accurately estimating cloud motion from a sequences of satellite images. Due to the complexity of cloud motion, which is a non-rigid movement and implying non-linear events, we cannot adopt some simple motion models and need to develop new algorithms. We presented a new method for cloud motion measurement based on image matching. We use the Iterative Multigrid Image Deformation (IMID) technique to measure the cloud movement at sub pixel accuracy, and for the alignment of image sub-regions differing in translation, rotation angle, and uniform scale factor, we change the correlation method from discrete Cartesian cross correlations to the phase correlation based on the Fourier-Mellin Transformation (FMT) which is invariant to translation, rotation and scaling. The phase correlation based on FMT can directly estimate the rotation angle and scale factor between satellite images. For cloud regions with large rotation angle or scale factors, our method can get more accurate motion estimation than traditional correlations by searching the deformation parameters using Cartesian cross correlation. In addition, the iterative multigrid framework aims at improving the precision of motion measurement by refining the size of cloud regions. To validate the performance of our algorithm, we process a cloudy satellite image with known geometric transformation, including translation, rotation and scaling to simulate a sequence of satellite images, and apply our method to measure the velocity fields of clouds. We also apply our algorithm to the sequence of real satellite images. Our results show that IMID technique with FMT can significantly decrease the displacement error compared to traditional correlation methods, especially in regions with large velocity gradients or high rates of rotation.
An optimization method for improving the accuracy of centroid computation based on Shack-Hartmann wavefront sensor
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The Shack-Hartmann wavefront sensor is widely used because of high light energy utilization and the simultaneous measurement of the optical wavefront phase distribution and intensity distribution. The accuracy of the centroid computation has a great influence on the detection accuracy of the Shack-Hartmann wavefront sensor. In this paper, a new method is proposed to improve the accuracy of centroid computation. This method include three steps. First of all, we use a new sliding template method to locate the spot automatically and obtain the approximate center of the spot. Next, we take an adaptive threshold method. After the processing of subtracting the threshold , we use the center of gravity(CoG) method to calculate the spot centroid. A series of simulations are conducted to verify the effectiveness and accuracy of this new method. Compared with the widely-used optimum threshold algorithm and the CoG method, the new algorithm not only enhances the accuracy of centroid computation but also has strong stability.
Laser spot center location algorithm based on sub-pixel interpolation
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Precise location of laser spot in laser precision measurement is always an important research direction. Laser has the characteristics of good direction and small divergence, so it is widely used in aerospace, weapon systems and optical measuring and testing instruments. The accuracy of the laser spot center location can directly determine the precision of measurement. Aiming at positioning the center of laser spot, in the foundation of researching the limitation of the practical application of the common laser spot center location algorithm, this paper proposes a method of laser spot center localization based on sub-pixel interpolation, which can effectively improve the signal noise ratio (SNR) of laser spot image, reduce the influence of the background noise and thermal noise. The algorithm firstly uses the threshold value decision to exclude the interference of the light of the image, and then use the improved sub-pixel interpolation algorithm for image edge detection to obtain the edge image, and finally using the circle fitting method to obtain the positioning center. Through the experiment of processing of laser spot image, the results show that improved algorithm proposed in this paper has higher positioning accuracy than the traditional centroid, and satisfies the need of laser precision measurement in reliability, positioning accuracy and noise resistance and other aspects, at the same time, the computational complexity of this algorithm is low, can greatly save the system resources, and it can be used for the processing of the video images in the hardware and software.
Aircraft relative attitude measurement based on binocular vision
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With the development of computer vision and image processing technology, vision measurement has been paid more and more attention. In the aviation field, estimating the relative attitude of aircraft using computer vision is important in aircraft flight-refueling, target tracking and positioning. However, the existing methods to measure the attitude of aircraft have some problems. In this paper, we propose to use binocular vision measurement method to acquire the attitude data of aircraft. This method has the advantages of simple realization and high practical value, which can also be widely used in visional measurement applications.
Taylor series-based generic demosaicking algorithm for multispectral image
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Using coated mosaic video spectrometer to collect multispectral image which reduce the spectral information redundancy and data volume greatly and achieve real-time data transmission conditions. The mosaic video spectrometer imaging technique use a similar mosaic template to capture all the pixels and output a two-dimensional multi-spectral image with dozens of spectral information. The image is divided into a certain size of matrix in its field, and each pixel in the pixel matrix is only for one wavelength information response and every pixel response for different wavelength. The size of the pixel matrix block depends on the number of spectral segments, which results in a low spatial resolution of the single spectral segment image and the spectral information of each pixel absenting severely. Therefore, to reconstruct the complete multi-spectral image, we must estimate and interpolate the missing spatial information and spectral information by demosaicking multispectral image. In this paper, we present a novel demosaicking method to produce the high resolution multispectral image and reconstruct missing spectrum information in high accuracy. The proposed method computes the first-and second-order derivatives of the original single multispectral image to measure the geometry of edges in the image and the spectrum value of missing pixel. Two metrics are used to evaluate the generic algorithm, including the structural similarity index-measurement system (SSIM) for reconstruction performance and the procession time. Experimental results show that the demosaicked images present higher SSIM (more than 0.9) and comparable calculated time performance as traditional ways. This algorithm brings the greatest advantage that make up for the weakness of mosaick multispectral image and reduce the data transmission process cost and storage needs.
Study of underway salinity monitoring device based on optical refractive index measurement
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In ocean optics, salinity is an important inherent optical parameter to be measured. In the field of optics, refractive index (RI) is closely related to salinity. Through the real-time detection of the refractive index, we achieved the purpose of underway monitoring the salinity of seawater. We designed a refractive index measurement system based on optical total internal reflection. In this system, the detecting precision of the refractive index of the sea water reached 10-4. Through the conversion of the refractive index, we achieved in-situ measurement of the salinity. In 2016 summer, we accomplished a successful underway measurement in China Yellow Sea. The trends of the results from refractive index are basically agreed with the salinity measurements from electrical conductivity.
Visual and infrared image fusion algorithm based on adaptive PCNN
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As the third generation artificial neural network, pulse coupled neural network (PCNN) which consider the characteristics of neurobiology of time coding and spatial accumulation, getting incomparable advantages comparing with the traditional artificial neural network, has broad application prospects in image fusion. In recent years, improving traditional model and adaptive adjustment of key parameters of the model have become major focuses gradually. In this paper, a novel visual and infrared image fusion algorithm is presented based on a new modified PCNN model. The key parameter of linking strength of the model is calculated with the character of the input images adaptively. Firstly, the modified PCNN employs index map and threshold look-up table to improve traditional PCNN model. Threshold look-up table records the thresholds which correspond to the different iteration layers of the modified PCNN model. To improve the computing speed of modified model, the thresholds could be calculated before the modified model starts to compute, which reduces the computing burden of traditional model to get the thresholds. Index map records the firing time of the input image’s pixels during modified PCNN model computing. The values of index map represent the integrating results of similar pixels in space neighborhood of the input image, which reflect the global visual features of the input image. Then, aiding method is used to compute the value of linking strength of modified PCNN model. The linking strength represents the degree that the linking input modulates the feeding input of the current neuron. If the value of linking strength can be decided in accordance with the specific characteristics of the input images, better fusion performance should be gotten in theory. Considering visual image has more detail information of target and infrared image has more energy character of target, local entropy and local energy are combined with the linking strength parameter of modified PCNN model for visual and infrared image separately in the proposed method of this paper. Finally, original visual and infrared image are processed with the modified PCNN model by calculating the linking strength using above procedure. The image fusion rules based on the index maps of visual and infrared image are used to calculate the fusion image. In order to evaluate the performance of the proposed method, a large number of experiments are made. In the experiments, the typical image sets which selected in many related papers are processed with the proposed method and wavelet transform separately. The different fusion images are evaluated with subjective and objective criteria, including the average, standard deviation and spatial frequency. Average stands for average value of pixel’s gray level. Standard deviation manifests that discrete situation for gray level related to average value. Spatial frequency could measure the image details information. The calculated results shows that, compared to methods like wavelet transform, the proposed method can improve the objective criteria values significantly.
Mathematical analysis for image sampling process of CCD
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In the photographic process with Charge Coupled Device (CCD), the image sampling of CCD is important. Due to the previous incorrect mathematical descriptions of the sampling, a correct mathematical equation is given by analyzing the CCD image acquisition process. Comparing the previous and the given one, shortcomings of the previous are pointed out. Then, a detailed spectrum analysis of the image sampling is carried out which illustrates the influence of various parameters of CCD on image acquisition. The mathematical analysis can optimize the choice of the parameters of CCD in practical applications.
An algorithm of non-continuous gray-scale histogram enhancement based on the visual characteristics
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Infrared thermal image, with many noises, blurred details and large ranges, needs to be processed on human observation applications. As the dynamic range of the infrared detector data is usually much larger than that of the display device format, infrared image needs to be gray-scale compression before displaying to human eyes. In order to achieve a good vision-observation effect and to retain the major information at the same time, it is proposed an algorithm of non-continuous gray-scale histogram enhancement, based on the human visual characteristics.
Firstly, through researching on gray-scale characteristics curve of the human visual on the image resolution, it configures a “visual resolution histogram” (VRH), which has non-continuous gray scales determined by the gray-scale characteristics curve.
Secondly, it integrates both equalization method and order-mapping themes, to transform infrared thermal image into the format of continuous and even distribution on gray scales in visual resolution histogram. As well as, it proposes a “Central Segment Histogram Enhancement” (CSHE) to keep mean brightness effects on the visual system.
Finally, experiments show that the proposed algorithm provides rich layers and good resolutions of displaying image on human view, as well as reduces the adverse phenomenon of scale moderation in conventional histogram equalization theme.
Super-resolution imaging by dual patterned nonlinear illumination
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Structured illumination microscopy (SIM) breaks the resolution limit caused by optical diffraction, and nonlinear SIM can further improve the resolution with nonlinear effect. However, current nonlinear SIM methods such as Saturated SIM and Photo-switching SIM are unsatisfactory in biomedical imaging. The stimulated emission depletion (STED) effect is considered as a great nonlinear effect with fast switching response, negligible stochastic noise during switching, low shot noise and theoretical unlimited resolution. We propose an original nonlinear structured illumination microscopy based on both patterned excitation illumination and structured STED field (SSTED-SIM). Theoretical study and simulation results demonstrated that SSTED-SIM is capable of providing the ability of fast imaging speed, and low imaging noise at the same time compared with other nonlinear SIM techniques.
Robust multiframe images super resolution
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Super-resolution image reconstruction is a process to reconstruct high-resolution images from shifted, low-resolution, degraded observations. In the last two decades, a variety of super-resolution methods have been proposed. These methods are usually very sensitive to their assumed model of data and noise, which limits their utility. This paper reviews some of these methods and addresses their shortcomings. We propose an alternate approach using 1norm minimization and robust regularization based on a bilateral prior to deal with different data and noise models. This computationally inexpensive method is robust to errors in motion and blur estimation and results in images with sharp edges. Experimental results confirm the effectiveness of our method and demonstrate its superiority to other super-resolution methods.
Frequency dependence of negative differential capacitance in p-i-n InGaAs photodetector at room temperature
Yidong Wang,
Jun Chen
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The negative differential capacitance(NDC) of p-i-n InGaAs/InP photodetector has been clearly observed, and the frequency dependence of the NDC is established, which is a small signal mode based on the accumulation and emission of electrons in the potential well at the p-InP/i-InGaAs interface state. The change of energy band was taken into account at the p-InP/i-InGaAs interface with the variation of the bias voltage. The NDC phenomenon is contributed by the additional capacitance (CD), which is caused by the charging-discharging process in second energy state (Ed2) of the potential well. From this model, it is found that the NDC is more obvious with the decrease of frequency, which is consistent with the conclusion of the experiment. It is proved that the probability of electron capture/escape in the second energy state of the potential well is affected by frequency. When the capture/escape time of the charge in the potential well is shorter than the frequency of the testing signal, the electrons will leave the potential well and produce a surplus of capacitance. The calculated value is consistent with the experimental result obtained.
Analysis of time delay in the temperature control model of super-luminescent diode for FOG
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Aim at the obvious dependence on the differential parameter of Super-luminescent diode (SLD), the theoretical and experimental investigation of the SLD transfer function and corresponding control parameters have been done. Results indicate that, i) the transfer function between temperature of radiation chip and electric current of TEC has a time delay, which comes from the distance between thermistor resistance and radiation chip; ii) the further of the distance between thermistor resistance and radiation chip, the longer of the time delay, which more obvious dependence on the differential parameter; iii) through optimizing the differential parameter, high control precision could be achieved for all SLDs produced by different factories, which distance between thermistor resistance and radiation chip is much different. Above results could help to understand the source of the time delay and the function of differential parameter in the temperature control process of SLD.
Modeling and optimization of InGaAs photodetectors
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The modeling and optimization of several photodetectors by semiconductor simulation tool Silvaco Atlas are reported. First is the simulations of p-i-n InP/In0.53Ga0.47As/InP photodetector at low bias. How the dark current, photoresponse and the transient response are influenced by the doping concentration and thickness of the absorption layer are reported. Second is a two-terminal p-n-p heterojunction phototransistors (2T-HPTs) based on In0.53Ga0.47As/InP. To optimize the device performance, the adjustment of the doping level, width, and compositional grading of base, the effects of high-low doping in collector region and the insertion of a thin undoped InGaAs layer in the base region have been investigated. The last is a simulation for InGaAs/InAlAs separate absorption, grading, charge, and multiplication avalanche photodetectors (SAGCM APDs), study the effect of multiplication layer parameters on the operating voltage ranges of APD.
Phase extraction based on iteration algorithm with crossed fringes in phase measuring deflectometry
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In phase measuring deflectometry, two orthogonal sinusoidal fringe patterns are separately projected on the test surface and the distorted fringes reflected by the surface are recorded, each with a sequential phase shift. Then the two components of the local surface gradients are obtained by triangulation. It usually involves some complicated and time-consuming procedures (fringe projection in the orthogonal directions, accurate phase shifting).To avoid the complex process, a novel phase extraction algorithm with crossed fringes is presented in this paper. It is based on a least-squares iterative process. Both a numerical simulation and a preliminary experiment are conducted to verify the validity and performance of this algorithm. Experimental results obtained by our method are shown, and comparisons between our experimental results and those obtained by the traditional phase-shifting algorithm and between our experimental results and those measured by the Fizeau interferometer are made.
A self-adaptive remote sensing image enhancement method based on gradient and intensity histogram
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It is crucial to enhance the lower contrast Remote sensing images to obtain more details information for further remote sensing image processing and application. In this letter here, a self-adaptive remote sensing image contrast enhancement method has been proposed. The method is an improvement, based on gradient and intensity histogram equalization (GIHE) by using the advantage of histogram compaction transform (HCT). Firstly, we obtained two enhanced images by GIHE and HCT, respectively. Then furthermore, the two enhanced images were normalized with a self-adaptive paremeter, which based on standard deviation and mean of the gradient. Finally and then, we modified the normalized image by dual-gamma function for preserving the local details. It’s evidenced that the proposed method have more richer details and better subjective visual quality, compared with the other methods. The experimental results depicted in terms of PSNR, MAE and Q. Comparing with the other methods, the proposed method had richer details and better subjective visual quality.
Assessing the impacts of grain sizes on landscape pattern of urban green space
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As an important part of the city, urban green space (UGS) plays an essential role in enhancing human well-being by virtue of multiple environmental, social and economic benefits. Study on landscape pattern of UGS is a focal point and hotspot in landscape ecology. The latest studies demonstrated that landscape metrics provides an effective method in quantifying UGS pattern. However, the study of the scale effect of landscape metrics should be strengthened. The objective of scale related research in UGS is to determine the appropriate scale in the measurement and evaluation of UGS and to find the underlying mechanisms by use of the selected scales.
This study aims to identify the scale characteristics and scale domain of UGS pattern, and provide basic information for pattern analysis and scaling in UGS research. In this paper, taking the central urban area of Székesfehérvár in Hungary as an example, we firstly extracted UGS from WordView-2 multi-spectral image (2m), then obtained a series of grain sizes by upscaling, and finally calculated and analyzed the characteristics of different landscape metrics with varying grain sizes. In this study, both the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Green Index (NDGI) were used to ensure the accuracy of the green space extraction in high spatial resolution image. On the basis of green space extraction, the green space patterns at different grain sizes were obtain by the assembly of grid cells. A total of 20 grain sizes were selected in this paper, ranging from 2 m to 40 m with a step size of 2 m. Landscape metrics both under class and landscape levels, including Patch Density (PD), Percentage of Landscape (PLAND), Mean Perimeter-Area Fractal Dimension (FRAC_MN), Division Index (DIVISION), Cohesion Index (COHESION), and Shannon’s Evenness Index (SHEI) were calculated.
The results demonstrated that with the increase of grain size, the landscape metrics under class level and landscape level were significantly affected by the grain size, and there was obvious critical grain size. On the whole, 16 m is the critical grain size of the green space pattern, and the suitable grain size for landscape metrics calculation of UGS ranges from 2 m to 16 m. The responding curves were varied by landscape metrics. Some metrics had clear changing trend and obvious turning grain size, while the others also had obvious turning grain size, but without clear changing trend. According to scale inflexions and responding curves discussed in the paper, scale domains of landscape metrics were confirmed. Generally, from 2 m to 16 m was the scale domain of UGS pattern, which means that related ecological model of UGS can be scaled across this scale extent by ordinary transformation. The study of impacts of changing scale on UGS can provide a reference for understanding the ecological benefits of UGS and optimizing the green space pattern.
Study on nonlinear process of remote sensing camera imaging at visible wavelengths
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As the atmospheric environments get more complex, the surface characteristics are diverse, spaceborne remote sensing cameras with the characteristics of large aperture, long focal length, and small size are demanded ever-increasing, and the high-sensitivity photoelectric detectors are required to detect more observing targets, the nonlinear process of remote sensing imaging system is worth consideration. In this paper, time delay integrated charge-coupled device (TDICCD) is used as an example to analyze imaging chains of space remote sensing system at visible wavelengths. The nonlinear process influenced by atmospheric radiation transmission mode, the reflection characteristics of earth surface, ground-air couping effect, imaging optical system, TDICCD photoelectric detector, imaging electronics system, data transmission/compression system, and ground station system is researched in detail. At the same time, the method to reduce the nonlinear effects of the image is discussed. In order to apply the space remote sensing information to all walks of life effectively, the nonlinear process will be improved by high-precision atmospheric radiation transmission calculation, reducing the move of the image plane and the noise of the electronics system, designing the A/D converter with stable gain coefficient, optimizing the compression/decompression process, and reducing information loss of the remote sensing imaging system from satellite to the ground station system.
High-precision attitude angle measuring system based on Talbot interferometry
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A traditional tracking device obtain the attitude angle by analyzing the spots position on photodetector. However, the attainable angular measurement accuracy depends on the field of view (FOV), number of pixels of the photodetector and the centroiding algorithm. In this paper, we present a high-precision attitude angle measuring system based on Talbot interferometry using cross-gratings and four wedge plates, which can acquire the real-time change of incident angle along two axis. The specific structure of the system is introduced, and the formula for calculating the relative angle is derived. The tracking accuracy is analyzed to be better than 0.2 arcsecond, which is dependent on the grating period, the distance between the two gratings and the gray scale of image. The Simulation results show that the RMS error of relative angle is better than 0.1 arcsecond both in x and y direction.
Design of an off-axis reflective zoom optical system
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With the limit of optical materials, it is difficult to design zoom optical systems which have long focal length by refractive systems with a simple configuration. All-reflective zoom optical systems could be lightweighted, compact and free of chromatic aberrations, and reflective optical systems can be unobscured by off-axis mirrors and have very good application foreground. In this paper, an all-reflective zoom optical system was designed, the all-reflective zoom optical system worked in the band of 400~1000nm, the diameter of the pupil was 100mm, the F number was 6~15, focal length varied from 600~1500mm, field of view (FOV) was 2°×0.8°~0.8°×0.48°. The pixel size of detector was 10×10μm. The result showed that MTF was higher than 0.3 at 50lp/mm and the quality of the optical system approached the diffraction limit, which met the design demand.
Automated and standardized high-resolution appearance imaging system for electronic components
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The rapid development of electronic industry not only increases the variety of electronic components, but also increases the difficulty of inspection work. To effectively improve the appearance inspection performance, an appearance imaging system based on machine vision is proposed in this paper. The system provides practical solutions for the following four problems. Firstly, to maintain the consistence of appearance images, a standardized imaging method is presented to unify imaging parameters. Secondly, when dealing with different reflection properties, we proposed a combined illumination method using light sources with different wave lengths to meet imaging needs. Thirdly, for large size objects, we put forward a method combined with size measurement and image mosaic to get high-resolution and panoramic images. Fourthly, this paper provides a method of 3D reconstruction based on monocular vision to reflect depth information and geometric characteristics of real scenes. In the meanwhile, we design associated software to achieve the auto-control. Experiment results conclude that it is effective to achieve standardized and high-resolution appearance imaging. The system builds up a good foundation for the subsequent inspection work. The research of this paper has a broad meaning and application prospect.
Denoising differential column image motion lidar signal using singular value decomposition
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Differential column image motion lidar (DCIM lidar) is a recent turbulence monitor for acquiring atmospheric turbulence profile based on active beacon. By imaging the differential column onto a CCD, DCIM lidar can obtain the Fried’s transverse coherence length (r0) of different altitudes with a high spatial and temporal resolution. Atmospheric turbulence profile can be recovered from r0 profile based on the integral relationship between r0 of spherical wave and the refractive structure constant (C2n ). In order to ensure the retrieved precision of atmospheric turbulence profile, singular value decomposition (SVD) is used to denoise r0 profile before inversion. The theory of DCIM lidar and SVD denoising is described. The Hankel matrix is constructed from the noisy signal and then the SVD is used to obtain the singular values. The rank reduction parameter is determined from the sharp variation of singular value curve. The denoised signal can be reconstructed by choosing the bigger singular values according to the rank reduction parameter. The numeric simulations and experiments are both carried out to validate the denoised method of SVD. The results show that the SVD can increase signal-to-noise ratio of r0 profile, thus enhancing the accuracy of the recovered atmospheric turbulence profile.
Design on high-current pulsed electron beam modification and analysis of machining characteristics for spinel
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Spinel (MgAl2O4) is an ideal material for infrared window and dome,which plays an important role in infrared imaging terminal guidance. Due to the uneven grain size, the flexible polishing surface of the spinel has grain morphology, which significantly affects the surface quality. In this paper, uniform surface modification of spinel by high-current pulsed electron beam(HCPEB)is investigated. On that basis, flexible polishing is carried out. A new way is provided for reducing and eliminating the grain morphology of the flexible polished surface.
Firstly, the mathematical model and numerical simulation for temperature field of spinel modified by HCPEB is carried out. The optimized modification parameters for spinel remelting are obtained: the irradiation energy density is 2J/cm2 and the irradiation time is 5μs. Then, the spinel is modified on the high-current pulsed electron beam equipment by using those parameters. The change of infrared transmittance is examined on a high resolution spectrometer before and after modification. The modified spinel is polished on magnetorheological finishing machine. The surface morphology and roughness of modified layer is observed on the Zygo white light interferometer after polishing. It is found that the grain is refined and the surface roughness is reduced from Ra 13.28nm to Ra 8.86nm.
Design of low-light-level resolution testing and comparing system
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In the comparison and selection of high-sensitivity detectors, the sensitivity, imaging contrast and resolution are important indicators to evaluate the imaging capability. The standard test method of resolution has a high demand for the environment and complicated and inconvenient. In this paper, we introduce a low-light-level resolution testing and comparing system to facilitate and compare and evaluate the sensitivity, imaging contrast and resolution of different high-sensitivity detectors, and provide the basis for the selection of the detector. The pattern of the target plate is designed. The target plate is made of an optically chrome-plated plate and the inner wall of the enclosed system where the optical system is located is coated with a black diffuse paint to reduce the interference of the stray light to the test. According to the sampling theorem, in order to ensure that the narrowest stripes after imaging meet the resolution testing requirements of the detector which has the smallest pixel, the narrowest stripe width of the imaging on the photosensitive surface should be less than 1/2 of the smallest pixel. The use of focusing makes it can still be clearly imaged when there is a small assembly error, but the focusing should not affect the test results. Finally, the system is used in an experiment, testing and comparing the resolution and sensitivity of three detectors, and verify the effectiveness and convenience of the system.
SO2 Differential Absorption Lidar System Based on Dye Laser
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The differential absorption lidar (DIAL) is a powerful and convenient tool for detecting the atmospheric trace gases. Based on dual wavelength differential absorption principle, we develop a set of lidar for measuring the concentration and distribution of the atmospheric SO2. This paper introduces the software, hardware and specific parameters of each subsystem in detail, then horizontal and vertical azimuth detection results are given. This lidar system adopts two tunable narrow linewidth dye lasers which pumped by Nd:YAG lasers, and produces l 600.10nm laser and 603.00nm lasers alternately. The lasers are frequency doubled by two second-harmonic crystals respectively and marked as λon=300.05nm and λoff=301.50nm which corresponds the strong absorption wavelength and the weak absorption wavelength of SO2 absorption spectrum. They are merged into one beam, and then expanded twelve times, and transmitted into the atmosphere coaxially with telescope finally. The back scattering signals are received by telescope system and converted into electrical signals by photomultiplier tube (PMT) after being collimated and filtered. These electrical signals are obtained by A/D acquisition card and stored in the computer for retrieving the concentration and distribution of the atmospheric SO2. Some field experiments are conducted in Huainan Atmospheric Science Research Institute, and we get some satisfactory results. On June 28th, 2016, the mean concentration of atmospheric SO2 is about 3.7 ppb in the range from 0.8km to 3.0km in horizontal azimuth. It conforms with the result of ground instrument from meteorological department. The vertical orientation detection is also performed at night of June 28th, 2016, and the atmospheric SO2 fluctuates in 0-5ppb which mainly exists below 1.5km.
Influence of haze on the performance of ground space optical communication
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This paper analyzes the influence of haze on the performance of ground space optical communication (GSOC). Firstly, the scattering model of haze aerosol is established based on the coated scattering theory of Christian Mätzler. Then the fitting relationship between atmospheric visibility V and PM 2.5 is obtained according to the Meteorological Bureau of Beijing. In order to calculate the attenuation coefficient, the relationship between spectral distribution of aerosol particles and PM 2.5 Index is derived. Finally, the effect of haze on GSOC with different detectors and modulation modes are discussed. The result shows that with the increase of PM 2.5 Index, the received optical power, sign-to-noise (SNR) and channel capacity (CAP) decrease rapidly, and bit error rate (BER) increases rapidly. In terms of wavelength selection, under the same detector and modulation mode, the effect of haze on the GSOC of the 0.86um laser is greater than that of the 1.55um laser. In the modulation method, the use of Binary Phase Shift Keying (BPSK) modulation is better than the use of Quadrature Phase Shift Keying (QPSK) in order to reduce the BER, while the worst modulation is to use On-Off Keying (OOK). When the sensitivity of the detector is -35 dBm，the value of PM 2.5 corresponding to 1.55um is not higher than 557, and the value of PM 2.5 corresponding to 0.86um is not higher than 548.
Research on the centroid detecting accuracy of stripe
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The centroid detecting accuracy of the stripe has an important influence on reconstruction and configuration of object structure in structured light 3D scanning measurement system. This paper analyzes the influence of several factors on the accuracy of stripe centroid detection. The pictures are grouped according to the peak signal-to-noise ratio and the stripe width. The gray-scale matrix is read out by Matlab, and then the centroid position is calculated by using the gradient centroid algorithm for the gray scale image by subtracting the threshold from the window. Finally, the accuracy of each group of images is evaluated by its standard deviation. The standard deviation of the group image is taken as the evaluation criterion, and the influence of PSNR and the stripe width on the accuracy of centroid detection is obtained. The experimental and simulation results show that the narrower stripes are more able to achieve higher accuracy; the accuracy is improved as the signal to noise ratio increases and multi-frame stacking can significantly improve the detection accuracy. The variation curves of the factors on the accuracy are given in the text. At the same time, the phenomenon that the measured value is fluctuating under a peak signal-to-noise ratio is analyzed by simulation. The results show that the fluctuation is consistent with the normal distribution.
Adaptive segmentation method based on similarity of laser point cloud topology
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Laser point cloud segmentation is the basis of target splicing or recognition. In this paper, a point cloud segmentation method based on point topology is proposed. The relationship between neighboring points is obtained by the curvature relationship between points. The relationship within point cloud between each point is established, and then the point cloud is divided by cutting the graph. The feature of eigenvalue of the Laplacian matrix realizes the adaptive segmentation. Three different kind of point cloud are tested with the algorithm in this paper and the result show that the algorithm has good performance on point cloud cutting of obvious characteristics and robust to noise.
Design and engineering development of single-mode fiber coupling system for Laser Doppler Velocity Radar
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Coupling of scattering light in space into a single-mode fiber is a key technology in the process of developing the Laser Doppler Velocity Radar. In order to make sure that the radar can get the longest detect distance, we have discussed the method of determining the key parameters of the receiver/transmitter common-path optical system based on the singlemode fiber coupling, from the points of laser radar detect distance equation, principle of single-mode fiber coupling efficiency reach maximum, and considerations of laser transmitter. In the engineering development process of an laser Doppler velocity radar, we have designed the optical system which fulfills the requirement of detect distance bigger than 3Km, then given out simulation results of single-mode fiber coupling efficiency versus lens spherical aberration, fiber defocus and fiber tilt. The tolerance analysis result indicates that the coupling efficiency will bigger than 52% under the usual levels of optical manufacture and assembly. At last we designed specialized equipment for testing the single-mode fiber coupling efficiency of the system we developed, the results showed that after mechanical vibration and thermal experiments, the single-mode coupling efficiency is 55.9%, and in the operating temperature range of 20±3°C, the lowest coupling efficiency is 45%, which is still bigger than 35% as the system required to make sure the detect distance bigger than 3Km.
Infrared radiation measurement technique for low-temperature target in TV (thermal-vacuum) conditions
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Aiming at the requirements of low-temperature measurement of spacecraft in thermal vacuum or thermal balance test, on the basis of the principle of infrared thermal measurement, the factors influencing the cool measurement of the infrared system were detailedly calculated and analyzed, from the targeted radiation, background radiation and radiation sensitivity of the detector infrared by the infrared system. It was found that the stray radiation of the optical system was the key link to restrict the cool measurement capability of the current hot test. On this result, a set of infrared thermal imaging system was designed, which could be used directly in the vacuum thermal test environment. In the optical system, the temperature could be cooled into -60°C. The blackbody was used to radiate and calibrate the system. As the experimental result showed, the system could be used to realize the infrared radiation measurement of the 150K cool target, which filled the blank of the technical field in china.
Imaging performance comparison of novel CMOS low-light-level image sensor and electron multiplying CCD sensor
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Due to its advantages on the cost, power and size, the study of the CMOS image sensor is considered as an important direction of the development of low-light-level image sensor. However, the sensitivity of current CMOS image sensor does not satisfy the low-light-level application requirements. This paper introduces several key techniques on how to improve the sensitivity of CMOS image sensors. We introduce a novel CMOS low-light-level image sensor based on Geiger mode avalanche photodiode (GM-APD) and digital TDI technology. Noise characteristics and complete signal-tonoise ratio(SNR) theoretical models are constructed for both sensors. A comparison of SNR performance of two image sensors is also done by numerical simulation in this paper. The results show that the novel CMOS low-light-level image sensor outperforms EMCCD at the very low light level.
Design of cryogenic area blackbody in vacuum chamber
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Blackbody is a crucial device for performance test and radiometric calibration of infrared system. This paper put forward a low-temperature surface blackbody with variable temperature. It works under vacuum and low temperature environment, and can realize the variable temperature control within the range from 130K to 450K by the dual control of liquid nitrogen and electric heating. This paper gave a detailed introduction to the system composition and structure of surface blackbody, introduced the design processes of radiator, temperature controller, temperature control system and other important parts, and analyzed the temperature field distribution of blackbody radiator through finite element software. And test method was used to test performance of the surface blackbody. The results show that the blackbody has good temperature uniformity and temperature stability performance, and is able to provide a benchmark for low temperature test of infrared system.
Study on time-frequency characteristics of transient response of the dynamic gratings in erbium-doped fiber
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The time-frequency characteristics of the transient response of dynamic gratings in erbium-doped fiber are different from stable gratings, which make it has great application value in the fields of fiber laser and optical fiber sensing. In consideration of the time domain characteristics, a time domain response model was built, which was based on metastable Er3+ population rate equation and light field transmission equation. The model simulated the process of establishing dynamic gratings in erbium-doped fiber with time sequence. And the theoretical results showed that the formation time of the dynamic grating gets shorter with higher pump power and shorter Erbium-doped fiber length within the effective length limits, which was consistent with the experimental results obtained by the so called “Strong light and weak light alternation” method except that the measured formation time decay ranges obviously migrated to lower pump power relative to the theoretical results. In consideration of the frequency domain characteristics, the transient two-wave mixing process was approximately simulated by using four-wave mixing equation. The transient reflectance spectra obtained through numerical calculation reflected the evolution rule of the dynamic gratings, which were coincident with the experimental results gotten by the rapid optical frequency modulation method. Under the condition of 1.8m Erbium-doped fiber, the experimental results showed that the turning saturated pump light power from the absorption type dynamic gratings to the gain type ones is about 0.05mW, the maximum relative reflectance variation of the gain dynamic gratings (3%) is 3 times of the absorption types. The measurement results have important references to the practical application of Erbium-doped fiber dynamic gratings.
Method and apparatus for measurement parameters of wheel set based on 1D laser sensor and magnetic grid sensor
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With the unceasing speedup of the train in China, traffic safety has been closely related to people’s livelihood. As elements that determine the reliability and safety in railway traffic, wheel set must be detected with much accuracy. Based on scanning method, a portable measuring system for measuring profile of train wheels is presented in this paper. Scanning part, which is pulled manually, consists of an 1-D laser sensor, whose accuracy reaches 0.05mm, and a magnetic grid sensor, whose solution reaches 0.05mm. Every 0.05mm of magnetic head movement will make the 1- D laser sensor send its current data to the tablets to get the wheel profile. The geometrical parameters, including flange thickness, flange height, rim width and QR (which is representative of vertical wear) can be calculated once the scanning is done. The systematic errors and the random errors have been analyzed in this paper. After the error compensation, the repeatability error is below 0.05mm, and the measurement accuracy of each parameter is below 0.1mm.
The waveguide effect on the diffraction wave in pinhole point diffraction interferometer
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As a high accurate measurement for wavefront metrology, the point diffraction interferometer(PDI) has been developed to overcome the accuracy limitation in traditional interferometers enabling the measurement precision in the order of a subnanometer. The PDI employs a nearly ideal spherical wavefront generated by pinhole diffraction as the reference wavefront, and is expected to be a powerful tool for high-precision optical testing. The diffraction reference wavefront is the key factor which determines the achievable precision in the measurement. In order to achieve high measurement accuracy precise characterization of the properties of diffraction wave is required. The structure of the pinhole functions as a cylinder waveguide and the fields in the pinhole are described as sums over waveguide modes whose behavior are determined by the interaction between the sidewall and the light. The pinhole functions as a cylindrical waveguide, in the way it determines the light field in the hole and the properties of the diffraction wave. In the paper, we make clear the physical mechanism of pinhole diffraction. The vector diffraction theory and the field equivalence principle are discussed. The field in the pinhole is analyzed according to the waveguide theory, and the waveguide effect on pinhole diffraction transmittance is discussed. Our results provide an important theoretical reference for design of the PDI system.
Dual plane on-axis digital holography with dual wavelength phase unwrapping
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Dual plane on-axis digital holography based on LCOS spatial light modulator with the benefits of dual wavelength phase unwrapping method is presented. Computer-generated chirp like complex reflectance were displayed on LCOS spatial light modulator for recording of holograms at two slightly displaced planes for two wavelengths which were later processed to suppress the dc term and twin image in the reconstructed image of each wavelength. The dual wavelength phase unwrapping method is used on the reconstructed wrapped phases of each wavelength to successfully unwrap the surface profile and result is verified by comparing it with measurement made by the optical profiling system.
Study on the irradiation precision analysis and index decomposition technology of photoelectric system
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The precision of the laser-guided weapon is affected by the irradiation precision of the laser designator. In the past, the influence analysis of the irradiation precision is often analyzed based on the experience with several main influencing factors and improvement measures are usually considered. In this paper, the general model of the influence factors of the irradiation precision is established by using the system engineering method from the range of the laser-guided weapon strike link, and then the problem of the performance index decomposition based on the irradiation precision come down to decision problem. A semi - quantitative model of Fuzzy-AHP integrating the analytic hierarchy process(AHP) and the fuzzy comprehensive evaluation(FCE) is proposed, which can guide the index allocation of photoelectric platform according to the importance of influencing factors.
Study on the distribution of biomolecules in different layers of porous silicon microcavity biosensor
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Porous silicon has many advantages, such as biodegradability, biocompatibility, tunable pore size and active covalent and non-covalent surface chemical properties. One-dimensional porous silicon photonic crystal microcavity structure has the characteristics of porous silicon and optical microcavity, it is compatible with existing silicon micromachining technology and can be embedded into the sensitive chip so as to realize the function of micro-nano detection devices and integration. At present, there are many biosensors based on existing porous silicon microcavity, through controlling the pore size of porous silicon microcavities, the biological target molecules penetrate into the porous silicon microcavity structure, leading to increases of refractive index of porous silicon layers. In the practical test, we found that the penetration of biological molecules in the microcavity is not uniform, it is difficult to enter into the deeper porous silicon layers, according to this, the paper will explore the distributional characteristics of different biological molecules in the microcavity, and the variation of the sensing efficiency under the circumstance of nonuniform increase in refractive index. This study will be helpful to the accurate design and theoretical development of high efficiency porous silicon microcavity biosensor.
Color image super-resolution algorithm based on SVM classified learning
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Due to the limitations of image capture device and imaging environments in traditional imaging process, high-resolution (HR) images are difficult to be obtained. The method of digital image processing can be used in image super-resolution with one or an image sequence in original conditions to reconstruct HR images which over the range of imaging system. Traditional learning-based super-resolution algorithm need to run through the sample library with a high computing complexity, and a high recognition rate in the scene with small shifts. This dissertation is mainly about color image SR and parallel implementation of the SR algorithm. An algorithm based on SVM classified learning is proposed in this paper.
Uncertainty analysis of spectral radiance scale realization
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In 2011, new primary standard apparatus of spectral radiance was setup at Changping campus of NIM based on high temperature blackbody BB3500M and double-grating monochromator of M207D. The temperature of the BB3500M was measured by a LP4 thermometer with uncertainty of 0.64 K at the temperature of 2980 K, which was calibrated by the Pt-C and Re-C fixed point blackbodies, and checked by a WC-C fixed point blackbody. The consistency of the temperature at 3021 K was better than 70 mK between NIM and VNIIOFI. The image of the measuring source was focused on the entrance slit of the monochromator with magnification 1:1. A mask was put in front of the entrance slit to limit the target spot size of the tungsten strip and the water-cooled aperture was 0.6 mm wide by 0.8 mm tall rectangle. The solid angle of spectral radiance measurement was approximately 0.008 sr. Uncertainty of spectral radiance scale realization was analyzed in this paper. The source of the uncertainty scale includes repeatability of the signal ratio of the blackbody and the transfer lamp, lamp alignment, temperature measurement of HTBB, non-uniformity of HTBB source, instability of HTBB source, correction of different size of source (BB and lamp), nonlinearity of the measurement system, current passed through the transfer lamp, wavelength error, polarization effects, bandwidth etc. The measurement uncertainty (k=2) of spectral radiance was 1.8 % at 250 nm, 0.90 % at 400 nm, 0.64 % at 800 nm, and 1.3 % at 2500 nm respectively.
The application of bioinspired photosensitivity enhancer on space remote sensing
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Inspired by the retinal structure of elephantnose fish, bioinspired photosensitivity enhancer (BPE) with many pyramid microphotocollectors can enhance the image intensity and the imaging capability under low light conditions. To study the application of BPE on space remote sensing, this paper introduced BPE into remote sensors and analyzed several parameters such as ground sampling distance, signal, noise, signal to noise ratio and so on in normal and low light conditions and compared BPE with binning technology. The results showed that, as an optical enhancing method, BPE has better performance than binning technology. The detectability of conventional systems under low light conditions could be improved by placing BPE in front of the sensors.
Modeling and simulation of corner-cube reflector: effect on coaxiality detection accuracy
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When the four-quadrant detector is detected using the pyramidal prism to reflect the light, the dihedral angle error causes the spot offset. In this paper, the relationship between the reflection spot offset and the three dihedral angle errors is analyzed by combining the pyramid model with the detector detection principle, and the influence of the dihedral angle error on the center shift of the reflected light spot is explored qualitatively and quantitatively. The simulation results show a high degree of central symmetry, which can be used to eliminate the system error resulting from the dihedral angle error of the corner prism, in order to minimize detection accuracy to 0.1μm. In addition, The simulation results provide a theoretical basis for the subsequent coaxial accuracy test.
Automatic detection of cloud in high-resolution remote sensing images based on adaptive SLIC and MFC
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Reliable cloud detection plays an important role in the manufacture of remote sensing and the alarm of natural calamities. However, it makes the task difficult with high-resolution remote sensing images with complex background and various types of clouds with different concentration, color and shapes. Related works mostly used gray, shape and texture features to detect clouds, which obtain results with poor robustness and efficiency. To detect cloud more automatically and robustly, we propose a novel could detection method based on the fusion of local optimum by adaptive simple linear iterative clustering (ASLIC) and the whole optimum by bilateral filtering with an improved saliency detection method. After this step, we trained a multi-feature fusion model based support vector machine(SVM) used geometric feature: fractal dimension index (FRAC) and independence index (IDD) which is proposed by us to describe the piece of region’s spatial distribution, texture feature: we use four angles to calculate the gray-level co-occurrence matrix (GLXM) about entropy, energy, contrast, homogeneity, spectral feature(SF): after principal component analysis(PCA) we choose the first bond, the second bond and the near infrared bond(NIR). Besides, in view of the disturbance of water, ice, we also use NDVI and HOT index to estimate the model. Compared to the traditional methods of SLIC, our new method for cloud detection is accurate, and robust when dealing with clouds of different types and sizes over various land satellite images.
Algorithm based on wavelet transform applied in the Space Infrared Image
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In view of the lack of precision and small dynamic range in one or two-point temperature nonuniformity correction method which is applied in the Space Infrared Image, this paper will introduce the technique of discrete wavelet transform which is applied to the non-uniformity correction. In addition, it is used the real-time infrared image processing method of removing blind pixels, invalid pixels and additive noise with using ground calibration parameters and deep space images. It is designed the infrared image processing method applied to the flight that the multiplicative noise in infrared image is turned into additive noise using the logarithm aimed at the characteristic of noise distribution.
An adaptive multi-threshold image segmentation algorithm based on object-oriented classification for high-resolution remote sensing images
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The object-oriented segmentation is a critical process in the classification and recognition of high-resolution remote sensing images. Multi-threshold segmentation methods have been widely used in multi-target recognition and information extraction of high-resolution remote sensing images because they are simple, easy-to-implement, and has ideal segmentation effect. However, the determination of thresholds for existing multi-threshold segmentation algorithms is still a problem, which limits to get the best effect of segmentation. To address this issue we propose a self-adapted multi-threshold segmentation method, based on region merging, toward segmenting remote sensing images. This method involves four steps: image preprocessing based on morphological filtering, improved watershed transformation to initiate primitive segments, optimal region merging, and self-adapted multi-threshold segmentation. The performance of the proposed algorithm is evaluated in QuickBird images and compared to the existing region merging method. The results reveal the proposed segmentation method outperforms the existing method, as indicated by its lower discrepancy measure.
Temporal high-pass filter non-uniformity correction based on guided bilateral filter for IRFPA
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In order to solve the problem of ghost artifacts in the traditional nonuniformity correction(NUC) method, a new scene-based guided bilateral filter(GBF) nonuniformity correction was proposed. In this paper, the original input image sequences are processed by the guided bilateral filter firstly, then the expected output imagine with the boundary information was estimated recursively only by using high spatial-frequency part of the image which contains most of the noise and nonuinformity. The method was verified with several infrared image sequences, and several experimental results show that the proposed method can significantly reduce the ghosting artifacts in temporal high-pass filter(THPF) and achieve a better nonunifotmity correction effect.
Positive absorption constraint based ptychographical algorithm with fast convergence rate
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Ptychography can reconstruct the complex amplitude distribution of the transmission object from the overlapped diffraction patterns. The extended ptychographical iterative engine (ePIE) algorithm is considered as one of the most popular phase retrieval algorithms of present time which has strong robustness and high image quality. However, no constraint is added in the iteration process, which results in slow convergence and makes the real-time imaging difficult. To overcome this problem, an efficient phase retrieval algorithm is proposed based on the constraint of positive absorption in the object plane where the absorption coefficient and phase distribution of the object are constrained by the positive absorption of the object. The simulation demonstrated that the proposed algorithm has greatly improve the convergence rate and imaging quality of traditional ePIE algorithm and is expected to be applied in real-time imaging.
A novel algorithm for maneuvering target detection under the high energy laser irradiating
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The high-energy laser weapon is famous for its unique advantage of speed-of-light response which was considered as an ideal weapon against Unmanned Aerial Vehicle(UAV). However, due to the high energy laser reflection effect, the pixel gray distribution of the frame image will be changed drastically, and therefore the miss distance signal will be interfered strongly when the high energy laser irradiating on the UAV, which seriously affects precision of object tracking in practical application. The traditional “centroid method” or “template matching method” have been difficult to meet the requirements of high precision miss distance which was less than 1pixel(RMS) under the reflected light interfering. In order to developing operational effectiveness of weapon system, G-DS(Gray weighted factor-Diamond Search method) algorithm was proposed which combined with gray weighted factor based on self-learning mechanism. It has been studied for the characteristics of UAV images by field experiment. The results show that G-DS algorithm is low-latency(less than 5ms), which can reduce time complexity compared with the traditional ME algorithm, furthermore, G-DS algorithm was robust based on local motion vector of the block, which can improve ability of target detection and recognition compared with the traditional “centroid method” or “template matching method”. Hence, G-DS algorithm was beneficial to the engineering of high-energy laser weapon.
Modeling and simulation of celestial background for dual-star-sensor testing
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With the increase in application of celestial navigation as well as the advances in computer graphics technology, modeling and simulation of celestial background is widely used in ground-testing of celestial navigation.
Celestial navigation is designed for star identification and confirmation of satellite attitudes in the space. A new celestial navigation technology is based on dual-star-sensor for the sake of high accuracy and reliability. Two star-sensors are set on the satellite, and there is an angle between the light axis of these two star-sensors. So these two star-sensors are designed pointed to the different direction in the space.
Modeling and simulation of celestial background which is used in the ground-testing for dual-star-sensor displays two different celestial scenes during navigation process by real-time graphics technology according to the two sensors’ orientation.
An introduction of resistive arrays and packaging technology
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As an important way to simulate the dynamic infrared scene, the technology of resistive arrays, especially large format resistive arrays are developing very fast. Principle of resistive arrays is introduced. The unit cell is composed by two MOS transistors, a capacitor and a resistor. The resistor is the main element to make infrared radiation by heating. Key parameters, such as temperature, frame rate, uniformity and cross-talk are used to standard to evaluate the performance of the arrays. Several methods to improve the parameters is put forward. In addition, development and current situation of the packaging technology is discussed and analyzed in this paper. At last, the technology developments of resistive arrays and packaging are summed up and an outlook of the future is provided.
Design and implementation of ultraviolet imager for corona discharge detection based on solar-blind AlGaN focal plane arrays
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Corona discharges occur in high voltage electrical equipment in case of defects and damage, while ultraviolet(UV) light generated during discharge. High resolution imaging in the solar-blind UV bands has a lot of applications in corona discharge detection. A ultraviolet imager based on 320×256 solar-blind AlGaN focal plane arrays (FPA) was designed that work even in the sunlight, because the Cut-off wavelength of the AlGaN FPA is 280nm. The UV image signal processing system based on FPGA is composed of various function modules include the voltage bias, sequence drive, A/D data acquisition, non-uniformity correction, video transformation. Due to FPGA-based data acquisition and realtime image processing technology, the UV imager can operate at a rate up to 100 frame/s. The results show that the simulation high voltage ultraviolet image can be obtained by the UV imager. The image non-uniformity correction performed is one-points correction method to realize background subtraction. And the images show good uniformity and contrast. The UV image of the alcohol burner flame can be detected by the Ultraviolet Imager. Imaging quality was discussed which can be determined by signal-to-noise ratio (SNR), the integration time, the optics f/number and so on. The best imaging conditions were analyzed and the imaging system was designed and setup. The conclusion is proved that the ultraviolet imager based on solar-blind AlGaN FPA provides a new method for corona discharge detection of high voltage power transmission and distribution system.
Research on laser spot location algorithm in weak turbulence
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Laser communication has become the main driving force for the development of modern wireless optical communication technology with the characteristics of large communication capacity, good concealment and good directivity. Acquisition, pointing and tracking system which is refer to as the APT system is the key technology to the laser communication, and the detection and processing technology is one of the key technologies of APT system. The effect of scintillation and laser spot drift caused by atmospheric turbulence seriously affects the laser spot positioning accuracy of laser communication APT system, which will affect the performance of laser communication system. It is very important to choose the appropriate spot pre-processing method and the best method to improve the positioning accuracy of laser communication system. An ideal spot image with known center coordinates was generated artificially and the MATLAB was used to simulate the atmospheric turbulence to make the laser spot close to the real atmosphere. Chosing median filtering and mean filtering method to the denoising pretreatment to get filtered image. Using iterative threshold method to obtain the binary image. Through 3 common spot positioning method like the gray centroid method, circle fitting method and the Gaussian fitting method to calculate the centroid of the binary image. After getting the central coordinates, the results were compared and analyzed. Experimental results showed that mean filtering is better than median filter to filter noise of the laser spot. Compared with other methods, the centroid accuracy obtained by the gray centroid method had larger deviation due to the process of filtering the noise was not completely suppressed. The laser spot center calculating by the Gaussian fitting method were with higher positioning accuracy. According to the calculation results, the applicable conditions of different spot location algorithms were given.
Improvement of responsivity of GaN-based p-i-n ultraviolet photodetector by inserting a delta doped layer in active region
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GaN-based homojunction p-i-n ultraviolet (UV) photodetectors (PDs) with the conventional structure and delta doped layer in the p-n interface are investigated numerically. Using the delta doped n-type layer, the PDs exhibit much higher responsivity and almost does not affect the dark current as compared to conventional one. Simulation results show that the enhancement of the carrier injection from p-type region, which is the main reason behind the improved performance of GaN-based p-i-n PDs employing the delta doping. This beneficial effect is more remarkable in situations with higher p-cap absorption, such as devices with a thickness p-cap layer or devices with a higher Aluminium composition.
Multi-focus image fusion using spatial frequency and discrete wavelet transform
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Pixel-level image fusion, which is widely used in remote sensing, medical imaging, surveillance and etc., directly combines the original information in the source images. As a pixel-level method, multi-focus image fusion is designed to combine the partially focused images into one fully fused single image, which is expected to be more informative for human or machine perception. To achieve this purpose, an algorithm using spatial frequency (SF) measure and discrete wavelet transform (DWT) for multi-focus image fusion is proposed. In this work, the source images are decomposed into low frequency components and high frequency components by using DWT. Then the spatial frequency of the low frequency components is calculated. The spatial frequency is used to judge the focused regions, followed by the morphological filter and median filter. The fused low frequency can be obtained. And the high frequency components are fused using traditional method. Finally, the fused image is obtained by doing inverse discrete wavelet transform. To do the comparison, the proposed algorithm is compared with several existing fusion algorithms in qualitative and quantitative ways. Experimental results demonstrate that our method can be competitive or even outperforms the methods in comparison.
An algorithm for object recognition in hyperspectral remote sensing images and its application to lithologic feature extraction
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This study, aimed at the problems of spectrum waveform characteristic distinction, operation speed, and spatial detail, proposes an improvement in the algorithm for hyperspectral remote sensing feature recognition. Based on this, we propose a fractal signal algorithm. The performance, efficiency, etc., of the algorithm itself is tested using CASI hyperspectral data and hyperspectral remote sensing image lithologic characteristics of the study area are also extracted. The initial value of the signal, the iteration step length, and other characteristics of the fractal signal in hyperspectral remote sensing data were discarded in this study. To a certain extent, the fractal signal algorithm can refine the distinguishability of similar characteristics in hyperspectral, and when used for feature extraction from CASI lithology data it accurately extracted the surface lithology of exposed bedrock areas.
A method of plenoptic imaging with high resolution in turbulent atmosphere
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In this paper, we propose and demonstrate an improvement of plenoptic imaging configuration for high resolution imaging with wide field of view in turbulent atmosphere. For the improvement, the plenoptic imaging configuration is equipped with a high resolution conventional imaging system. Plenoptic imaging system is only used for measuring the wavefront distortion of imaging beams. Based on wavefront distortions measured by plenoptic imaging system and blurred images captured by the conventional imaging system, high resolution images can be achieved by the deconvolution of blurred images. Numerical simulations and experimental results show that the improved plenoptic imaging configuration can be used for restoration of near-diffraction-limited images of objects, successfully. Compared with conventional imaging system and plenoptic imaging system, the improved plenoptic imaging configuration combines advantages of wavefront distortion correction, high resolution imaging, wide field of view. The technology proposed in this paper can have wide applications in photo-electric theodolite and large telescopes.
Linear verification of model-based wavefront sensorless adaptive optics system
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In recent years, the wavefront sensorless adaptive optics (AO) system receives extensive research and the model-based control AO system as one of the most systems will become the most promising one. The model-based AO control system depends on a linear relationship between second moments of the wavefront gradients and masked far-field intensity distribution. Before investigating whether the model-based control algorithm has a good correction capability, the linear relationship must be verified. In order to testify the linear relationship, an adaptive optics system experiment platform is established with a 37-element deformable mirror and a CCD camera. The CCD camera measures the information of far-field intensity distribution and the Hartmann Shack gets sensor information of wavefront distribution. The linear relationship is analyzed based on above the information. Result shows that there is a linear relationship between second moments of the wavefront gradients and masked far-field intensity distribution and the slop is 0.018, which is very close to the theoretical value 1 / (4π2).
Self-adaptive histogram equalization image enhancement based on canny operator
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Traditional histogram equalization method always leads to the gray level reduction and loss of details. In this paper, an efficient and self-adaptive image enhancement algorithm is proposed based on canny operator and histogram equalization. The canny operator is used to extract the detail information which could be preserved in the enhanced image. The shortcomings of histogram equalization can thus be overcome. The experimental results with infrared images show that our method can preserve more image details and improve the image contrast and suppress noise effectively, which indicates a better performance for infrared image enhancement.
Comparative studies of wavelet threshold and complementary ensemble empirical mode decomposition in the denoising of differential column image motion lidar
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Differential column image motion lidar (DCIM lidar) can obtain the Fried’s transverse coherence length (r0) of different altitudes with a high spatial and temporal resolution. According to the integral equation of atmospheric coherence length (r0) of spherical wave, the refractive structure constant(C2n) profile can be retrieved from r0 profile. Aiming at improving the retrieval accuracy of atmospheric turbulence profile, noise reduction on r0 profile is implemented before inversion. Two methods of wavelet threshold and complementary ensemble empirical mode decomposition (CEEMD) are used to denoise r0 profile. The effects of denoised methods on r0 profile and C2n profile are investigated. The numeric simulations and experiments are both carried out to validate the two denoised methods. The results show that both the two methods can improve the signal-to-noise ratio (SNR) of atmospheric coherent length profile and reduce the recovered error of the atmospheric turbulence profile, and wavelet threshold method is superior to CEEMD method under different noise conditions.
An optimized acquisition approach exploiting geometrical calibration in x-ray cone-beam computed tomography
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X-ray cone-beam computed tomography, featuring high precision and fast-imaging speed, has been widely used in industrial non-destructive testing applications for the three dimensional visualization of internal structures. Due to mechanical imperfections, geometric calibrations are imperative to high quality image reconstruction. Currently, the twoball phantom-based calibration procedures exploiting the projection trajectories of the phantoms are the most commonly used approach for the estimation of the geometrical parameters and the calibration of CT system. However, an additional scan needs to be performed, even after each object acquisition when lack of system reproducibility, leading to multiplied calibration times. The emphasis of this paper is to optimize the process of acquisition in cone-beam CT imaging with minimal time, based on the understanding of the determination of the ball position in typical phantom-based geometric calibration algorithms. An applicable condition of the calibration algorithm for simultaneously scanning objects and calibration phantoms is proposed and demonstrated, which is that the minimum projection value of the scanned object needs to be at least 100 counts higher than those of the calibration phantom, with consideration of the system noise. The CT experiments are based on a laboratory industrial cone-beam CT system with a micro-focus x-ray tube (Thales Hawkeye 130) and a flat panel detector (Thales Pixium RF4343). Objects imaged are chosen with a wide projection value range, from low-Z watermelon seeds and high-Z materials, including a standard Micro CT Bar Pattern Phantom (QRM) for image quality assessment. In these experiments, objects, as well as two-ball phantoms, both placed in the field of view without overlapping in the vertical direction, are projected over 360 degrees, instead of scanning the calibration phantoms separately. Hence, the true geometrical relationship is resolved utilizing the two-ball algorithm. Both simulation and experimental results confirm that the calculated geometrical parameters will not be affected by the objects as long as their projection value difference meeting the requirements above. And the reconstruction image quality is almost the same with those by an independent calibration. Compared to the traditional application of the phantombased geometrical calibration method, the novel approach presented in this paper has obvious advantages from an imaging perspective, saving acquisition time and eliminating the undesired influence from the operation staff for the same cost.
An efficient iterative super-resolution technology for coded aperture imaging
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In this paper, we employ coded aperture imaging (CAI), an emerging computational technology that captures 4D light-field information to realize pixel super-resolution imaging via post-processing. Our CAI experimental setup is built based on 4f delay system with reflective optical path structure, where a programmable LCOS spatial light modulator is integrated at the Fourier plane to implement high-resolution high-contrast aperture coding, without requiring specialized hardware or any moving parts. In addition, we propose an iterative super-solution reconstruction algorithm based on aperture coding, optical fields manipulation and compressed sensing. First, we establish an accurate mathematical model for the OTF of coded aperture system and pixel binning process. Then, based on a series of low-resolution intensity image, we computationally reconstruct the high-resolution image with the convex projection iterative algorithm. The effectiveness of this algorithm is demonstrated with both simulation and experimental results. Due to its flexibility and simplicity, this technology can break physical limitations of the detectors’ resolution to one that is solvable through computation, rendering it a promising tool in public security, military survey, medical science and many other fields.
Optical system design of space fisheye lens and performance analysis
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In order to reduce the number of cameras which are equipped in spacecraft, and using a small amount of cameras to monitor the whole spacecraft, an optical system of fisheye lens is designed based on the principle of non-similarity. The optical system uses a high definition CCD which has 1920×1080 pixels (the size of pixel is 5.5μm×5.5μm). The effective focal length of the fisheye optical system is 5.0 mm, the F number is 5.0, and the full field of view (FOV) is 180°. Its modulation transfer function (MTF) in all FOV is more than 0.5 at 91 lp/mm with great image. And the relative illumination of marginal FOV reaches 85.2%, this guarantees that the optical system has a good of illumination uniformity. Taken into account that the camera will be used in the intricate space environment, the article was analyzed the influence of environmental factors, the changing temperatures and vacuum environment, on the imaging quality of the optical system. The results show that the optical system of fisheye lens still has good imaging performance under the temperature -40°C~+60°C in vacuum environment. In the imaging process, the stray light which likes a red ring has been found at the edge of the image when the strong light source appeared in the middle of the image, it is similar to a positive ghost. After analysis, the results show that stray light mainly comes from the reflected light among the lens surfaces. So, there is a proposal that the radius of these lens surfaces should be restricted under optimization. Through the further optimizing and experiment, the consequence proves that the stray light was successfully eliminated.
A novel remote sensing image fusion scheme based on NSCT and compressed sensing
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In this letter, we propose a novel remote sensing image fusion method based on the non-subsampled contourlet transform and the compressed sensing (CS) theory. [2][3] Method First, the IHS transformation of the multispectral images is conducted to extract the I component. Secondly, the panchromatic image and the component intensity of the multispectral image are decomposed by NSCT. Then the NSCT coefficients of high and low frequency subbands are fused by different rules, respectively. For the high frequency subbands, the absolute maximum selection rule is used to integrate high-pass subbands; while the adaptive regional energy weighting rule is proposed to fuse low-pass subbands. The sparse coefficients are fused before being measured by Gaussian matrix. The fused image is accurately reconstructed by Compressive Sampling Matched Pursuit algorithm (CoSaMP). Some experiments are taken to investigate the performance of our proposed method, and the results prove its superiority to the counterparts.
Fast triangle star identification algorithm based on uncertain sign
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As a fine star-field identification algorithm, triangle algorithm is used far and wide currently, but there are some defects in triangle algorithm, such as low search efficiency and high mismatches probability. In allusion to these defects, a new triangle algorithm based on uncertain sign is presented. This algorithm extracted F and R features of star triangle, and then built a guidance characteristic catalogue which was searched by means of k-vector, promoting the search efficiency, moreover, in order to avoid the occurrence of mismatch, this algorithm would verify guide star triangle’s auxiliary information if its uncertain sign is 1. Simulation shows that: compared to the traditional triangle algorithm, this algorithm has a couple of advantages, including the higher rate of correct star recognition, lower mismatches probability, and better real-time adaptability and robustness. And this algorithm can reach 97% on identification rate when the position error is 2 pixels, and average identification time is 38.74ms; the traditional algorithm is 75% when the position error is 2 pixels, and average identification time is 187.26ms.
Texture aware learning-based image fusion method for fixed focal-length cameras
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This paper aims to develop a novel approach of image fusion for an asymmetrical camera system when multiple images are acquired with cameras which have large differences in focal lengths but similar sensor size with an overlapping field of view. The fused image usually becomes perceptually unpleasant because the high-frequency components of a wideview image will be quite inadequate comparing to the tele-view images. Four steps are consisted in the proposed work: (i) image upscaling of the wide-view image, (ii) texture identification on the upscaled image, (iii) the performance evaluation of image upscaling, and (iv) the image inpainting for the high-frequency components of the wide-view image. The field of view of tele-view camera is set to be 4 times smaller than the wide-view camera in spatial angle in the experiment. The experiment result illustrates that the proposed algorithm brings significantly perceptual improvement to the wide-view image.
Infrared image watermarking based on the discrete shearlet transform
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This paper narrates infrared image watermarking based on the discrete Shearlet transform(DST). DST has nice multiresolution and multi-directional[1] analysis ability. This feature of DST can be exploited on image watermarking. the proposed method has two purposes. One is hiding watermark information into multi-direction coefficients of the host infrared image to make the watermark is imperceptibility. The other purpose is dealing with various attacks such as noise addition, enlarging, cropping, median filtering and Gaussian filtering to verify the robustness of this method. The experimental results show that the visual effect is satisfactory because the secret information can’t be distinguished by people’s eyes. In fact, through the correlation calculation also shows that the invisible effect is very good.
Progress in ultrasonic bonding wire process and quality evaluation of bonding point
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Wire bonding is one of the most widely used methods in the field of electrical connecting in packaging. The main characteristics of common wire bonding materials and process parameters affecting the reliability of wire bonding are discussed and analyzed. The evaluation method of wire bonding quality is described, and the measures to enhance the reliability of wire bonding are put forward. The results show that of all the wire materials, gold wire (Au) has the best comprehensive performance which used most widely. Aluminum wire (Al) and copper wire (Cu) are ideal materials for the replacement of Au because of low cost. Platinum wire (Pt) is mainly used in low temperature packaging for its low heat loss. In terms of bonding process parameters, bonding force is an important parameter for the shape and strength of bonding point. Adjusting the bonding force is an effective method to solve the problem of pad damage and bonding interface slip. Ultrasonic power and time are the important factors affecting bonding strength. Usually it is easier to bond wires with higher bonding temperature, and appropriate temperature is exist due to the device’s tolerance temperature. In the wire bonding quality evaluation methods, microscopic observation is the simplest method to evaluate the bonding quality. The mechanical testing methods include wire pull test and ball shear test. Environmental tests include temperature cycling, electromagnetic resonance test and other testing. It is mainly used to evaluate the overall performance and fatigue properties of wire bonding. As a result, the mechanical testing and environmental testing are the effective methods to adjust the new bonding process , and microscopic inspection is an effective method for bonding quality assurance.
Mixed pulse-Gaussian denoising algorithm for improving image quality in assembly inspection of nuclear power plants
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Visual inspection for nuclear fuel assemblies is necessary during outages of nuclear power plants. These inspections can be used to identify fuel assemblies’ anomalies that endanger the reactor’s running. However, intense radiation of fuel assembly sensitively degrades the image quality through a mixture of impulse and Gaussian noise. To solve this problem, an image denoising algorithm based on Non-Local Dual Denoising (NLDD) and Rank-Ordered Absolute Differences (ROAD) is proposed here. It consists of two steps. The detector ROAD is first used to find noisy pixels in an image damaged by impulse noise and replace them with neighborhood values. Then, NLDD filter is applied to image corrupted with Gaussian noise and retains the details. The proposed approach has been successfully tested on assembly inspection of nuclear power plants. The results reveal that our approach is effective to noise suppression and crucial detail preservation.
Design of ultra-low-power readout circuit for UV GaN focal plane array
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A Readout Integrated Circuit (ROIC) for GaN ultraviolet (UV) focal plane array (FPA) working in “solar-blind” band is studied in this paper. It has a format of 320×256 and a pixel pitch of 30μm. This circuit can operate both in integrating-while-reading (IWR) and integrating-then-reading (ITR) mode with the frame rate higher than 100fps. It is common that trade-offs always exist between chip power consumption and performances in integrated circuits design. In order to get high injection efficiency with small area and low power, A novel low-power capacitive-feedback trans-impedance amplifier (CTIA) with snapshot mode is designed for the proposed circuit. The smallest operational current of CTIA is only 10nA for 5V power supply. The total power consumption of ROIC is reduced significantly to 45mW with the ultra-low-power pixel. By adopting the 0.35μm 2P4M mixed signal process, the high-performance CTIA architecture can make two gain selections which charge capacities are 3.4Me - and 0.16Me - per pixel with 2.5 V output range. According to the experimental results, this circuit works well under 5V power supply and achieves 8MHz pixel-data-transmission rate.
Small target detection in infrared image using convolutional neural networks
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Infrared small target detection is an important research topic in the field of infrared image processing and has a major impact on applications in areas such as remote sensing, infrared imaging precise. Due to atmospheric scattering, refraction and the effect of the lens, the infrared detector to receive the target information very weak, it’s difficult to detect the small target in complex background. In this paper, a novel small target detection method in a single infrared image is proposed based on deep convolutional neural network that is mainly using to extract the features of target, through the method can obtain more discriminative features of infrared image. Firstly, the off-line training of convolution kernel parameters using open data sets and simulated data sets, the result of preliminary training gives an initial convolution kernel, this step can reduce the time required for parameter training. Secondly, the input infrared image is preliminarily processed by the trained parameters to obtain the primary features of the infrared image, through the processing of the convolution kernel, a large number of feature information in different scales of the input image are obtained. Finally, selecting and merging the features, design the efficient characteristic information selection strategy, then fine-tune the convolution parameters with the result information, by merging the feature graph can realize the output of the result target image. The experimental results demonstrated that compared with existing classical methods, the proposed method could greatly improve the quality of the results, more importantly, our method can directly achieve the end-to-end mapping between the input images and target detection results.
High dynamic infrared image compressive enhancement based on fast local Laplacian filters
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High dynamic range infrared image detail enhancement is an important processing procedure in the field of infrared (IR) imaging. Because of the dynamic range of natural scene image far beyond the human vision system, display equipment, and the high dynamic image transformed directly from high dynamic to low dynamic will cause detail information lost, it is essential to compress dynamic range of image and enhance detail. Aiming at the disadvantages of existing methods, high dynamic infrared image compressive enhancement based on fast local Laplacian filters were proposed. First, the fast local Laplacian filters are utilized to separate the image into a base layer and detail layer. Second, the dynamic range of base layer was compressed by using gamma correction in order to improve contrast. The detail layer is stretched by utilizing sigmoid function. Finally, the enhanced output image is obtained by recombining the detail layer and base layer. Compared with other methods such as histogram equalization, bilateral filtering, the experimental results demonstrated that the proposed method have a better performance in term of enhancing details and improving contrast by using evaluation index of image detail enhancement.
Topological derivative improved partial differential equation for infrared spectral data denoising
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To reduce the influence of noise in infrared spectral signal measurement, a topological derivative improved partial differential equation method for infrared spectral data denoising is proposed. As an indicator function, topological derivative through a minimization process to find the best position to introduce disturbance, where are spectral edge points, then select the most excellent diffusion coefficient, so the cost of the minimum functional value. Based on the idea of topological optimization, it makes the lowest topological derivative to be optimum one. Then the diffusion is applied by using partial differential equation. Several simulated infrared spectral sequences are utilized to verify the performance of the proposed method. The experiment results show that our method is better in denoising.
The preliminary discussion of bandwidth correction methods for spectral irradiance measurement of deuterium lamp
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Deuterium lamp is used as the transfer standard of air-UV spectral irradiance (200nm to 400nm). The CCPRK1. b comparison of spectral irradiance 200nm to 350nm took deuterium lamp as transfer standard lamp. Spectral irradiance is measured by a spectroradiometer with finite bandwidth. The bandwidth can cause measurement error. In order to correct the measurement error, we apply SS and DO bandwidth correction methods to the spectrum of Deuterium lamp. We obtain the correction effect preliminarily.
Optical design of wide-angle catadioptric lens for LWIR earth sensors
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Using progressive design method, we designed and built a wide field of view (FOV) catadioptric lens for LWIR earth sensors in the 14 to 16 μm range. The prototype lens is compatible with 640×480 uncooled FPA and 25 microns pixel pitch. Its full field of view is 170° and F number is 0.86. The f-theta distortion is less than 1%. Besides, the system works well during a temperature range of -40°C~+60°C.
Kernel regression based infrared image non-uniformity correction
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In traditional scene-based non-uniformity correction methods, ghosting artifacts and image blurring affect the response uniformity of the infrared focal plane array imaging system seriously and decrease the image quality. In order to suppress artifacts ghosting and improve image quality, this paper proposed a new based on kernel regression nonuniformity correction method for infrared image, because of its powerful ability to estimating. The main purpose of proposed method is to obtain reliable estimations of gain and offset parameters. Firstly, in order to suppress the ghost artifacts normally introduced by the strong edge effectively, this paper employs the kernel regression method to estimate the desired pixel value of each detector uint. Then the two correction parameters are achieved with the steepest descent method for the purpose of updating these two parameters synchronously. Finally, more accurate estimations of the two correction parameters can be obtained. Several simulated infrared image sequences are utilized to verify the performance of the proposed method. The results show that our method performs better than other compared methods.
A modified topological derivative based background suppression for infrared dim small target detection
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In the processing of infrared small target image which has low signal-to-noise ratio and complex background, the target detection and recognition are very hard. So, how to suppress infrared complex background in low signal-to-clutter addition becomes the key problem in the detection of infrared small target image. The topological derivative can quantify the sensitivity of a problem when the domain under consideration is perturbed by changing its topology. Considering the idea of topology optimization, a modified topological derivative based background suppression method for infrared dim small target detection was proposed. An appropriate functional and variational problem is related to the cost function. Thus, the corresponding topological derivative can be used as an indicator function leads to the processed image through a minimization process. Firstly, introduce perturbations to each pixel of the infrared image. Secondly, calculate the corresponding topological derivative. These pixels also have the least cost function. Finally, using the modified optimal diffusion coefficient to diffuse the pixels where the topological derivative is negative to make its background smooth and achieve the purpose of removing the background clutter while enhancing the small target. Compared with other several experiment results of existing background suppressing methods in indexes, the method the paper proposed has innovative ideas and gets well effects of background suppressing and are practical methods. All of above have the important research value for the related work in future.
Infrared/radar data fusion and tracking algorithm based on the multi-scale model
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Infrared and Radar data fusion algorithms have drawn a great deal of attention due to its implementation of complementary information, improvement of target tracking and enhancement of system viability. However, in the step of estimating the target state by multi-sensor, different sampling rates between two sensors make it difficult for data fusion. In order to solve this problem and make full use of the advantages of the data obtained by multi-sensor, an effective state estimation algorithm by combining the theory of multi-scale and converted measurement Kalman filter (CMKF) algorithm is presented in this paper. By establishing the multi-scale model, target state is estimated at the finest scale with the Interacting Multiple Model (IMM) algorithm at first. Then, at the coarse scale, appropriate observational information is selected in accordance with specific conditions. Angle information estimated by infrared sensor and the distance information obtained by radar sensor are fused to locate the target when two sensors have the same sampling time instant, otherwise, the target is located only by using the angle and distance information acquired by radar sensor. In addition, CMKF algorithm is used to estimate the target state and obtain the optimal fusion estimation. The simulation results under the environment of MATLAB show that the proposed algorithm effectively improves the precision and the instability of infrared/radar detection system.
Infrared image enhancement method for color transfer and contrast equalization in image registration
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The use of infrared sensors to detect and obtain the real image of the moving target is an important means for the test of weapon equipment and the monitoring of space launch. To better play the advantages of infrared devices visibility at day and night, the role of distance, solved the details of the image display effect by eye gray resolution constraints problem for ground multisensor surveillance system field situation awareness requirements, proposed color visible image and infrared image registration and image processing based on color transfer and contrast equalization enhancement method. First, analyzed the implementation of dynamic monitoring system based on ground live monitoring system, through the acquisition of color image and infrared image, and multi frame color images combining to construct the scene, established the acquisition, processing, application process of the visible-infrared image registration; Then, analyzed the representation of color transfer process of color space and the features of real-time processing, will color scene graph expressed as geometry, color space, comprehensive expression of brightness distribution, According to the correspondence between the infrared image and the color scene image, obtained the color space representation of the infrared image; Next, Improved the infrared image gray distribution by contrast equalization method, by contrast limited adaptive histogram equalization to improve the display effect of gray details. As for the validation of the proposed method, using the method in the paper to enhance the infrared image, the experimental results show that the integrated color transfer and contrast balance, improved the visual effect of image display and showed more details information, Presented more detailed information, improved the image display effect.
Motion estimation of sequence image based on feature extraction of extended objects
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SIFT feature point extraction algorithm is commonly used in image matching which maintains invariance for scaling, rotation, and brightness changes. Phase correlation algorithm is less dependent on image information with relativity strong noise cancellation performance and high robustness. Based on the traditional phase correlation method, a subpixel accuracy motion estimation method based on interest region is proposed to achieve the high precision localization of the extended object. The paper choose feature blocks centered on feature points extracted from SIFT algorithm. Then the phase correlation operation is performed on the obtained feature blocks and the initial amount of translation is obtained. Then interpolate and implement cubic surface fitting on the neighborhood of the correlation peak, the accurate translation of adjacent images is obtained. The paper simulate the classical pictures applied to image processing. The accuracy of the method is verified by the ideal data.
Extraction of low contrast optical spot in cloudy weather and influence on atmospheric coherence length data
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The atmospheric coherence length which reflects the intensity of atmospheric turbulence is a very important parameter of laser atmospheric propagation and adaptive optics. It has been used as the modern definition of atmospheric seeing in astronomical observations. Day-night atmospheric coherence length monitor is a conventional instrument which can measure the atmospheric coherence length. It uses the two aperture differential imaging motion method (DIMM) to measure the atmospheric coherence length r0 based on continuous observation of stars. When there are clouds in the sky especially for cloudy weather, the starlight are often obscured by clouds and the SNR of image is very low for only faint starlight received by Day-night atmospheric coherence length monitor. This would cause unacceptable measurement error. Therefore, there are fewer atmospheric coherent length data in the cloudy weather. The paper analyzes the measurement errors and tracking errors under the low SNR condition. Based on the experimental data, the characteristics of night cloudy sky background are analyzed. According to the fact that the sky background obeys Gauss distribution, we present an improved method of Gaussian spot extraction fitting method to extract the optical spot region. The processing method includes the following steps: first, the mean intensity of the image is calculated by Gauss fitting, then, divide the image into the background and the suspected target with the threshold of the half width of the Gauss distribution above the mean intensity. The largest area of the suspected target will be taken as the optical spot area. After that, a sliding window of 5 multiply 5 scale is used to scan the optical spot area to carry out gauss fitting for the center pixel xij at the angle of 0degree,45degree,90degree and 135degree. A comparison is taken between xij and the average values of the four fitting results, if the difference exceeds the threshold value, the pixel xij will be taken as the noise pixel, and the mean value of the fitting result is used to replace the pixel intensity. In order to verify the accuracy of the method, the turbulence phase screen has been used in numerical simulation. The result shows that this barycenter extraction method can accurately extract the centroid of optical spot under low contrast situation. Even when the SNR is 1.25db, the measurement error of r0 is still less than 10%. We believe that this method may be useful in improving the adaptability of Day-night atmospheric coherence length monitor to more kinds of weather.
Hyperspectral anomaly detection based on machine learning and building selection graph
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In hyperspectral images, anomaly detection without prior information develops rapidly. Most of the existing methods are based on restrictive assumptions of the background distribution. However, the complexity of the environment makes it hard to meet the assumptions, and it is difficult for a pre-set data model to adapt to a variety of environments. To solve the problem, this paper proposes an anomaly detection method on the foundation of machine learning and graph theory. First, the attributes of vertexes in the graph are set by the reconstruct errors. And then, robust background endmember dictionary and abundance matrix are received by structured sparse representation algorithm. Second, the Euler distances between pixels in lower-dimension are regarded as edge weights in the graph, after the analysis of the low dimensional manifold structure among the hyperspectral data, which is in virtue of manifold learning method. Finally, anomaly pixels are picked up by both vertex attributes and edge weights. The proposed method has higher probability of detection and lower probability of false alarm, which is verified by experiments on real images.
A star pattern identification algorithm based on wheel code feature
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Pyramid algorithm and grid algorithm are typical algorithms for all-sky autonomous star identification, and it has advantages of high recognition rate, and fast in running. However their recognition rate decreases rapidly when the position noise, lost stars or fake stars exist in the star image. In order to improve the performance of star sensor, a new star identification algorithm based on star pattern of wheel code is proposed. The algorithm combines the main star and its surrounding neighbor stars to form the characteristic unit, and then constructs the corresponding code feature and the wheel feature respectively. In the process of star matching, the algorithm uses the code feature of the observation star as an index to Inquire storage address of the candidate navigation star, and then calculates the similarity of wheel feature between the candidate navigation star and the observation. Simulation shows that: compared to the grid algorithm, this algorithm has higher rate of correct star recognition and better robustness. When the position error is 1 pixel and 2 lost stars exist in star image, this algorithm can reach 98.4% on identification rate, while the grid algorithm is 94.6%, and the pyramid algorithm is 83.5%; when the position error is 1 pixel and 2 fake stars exist in star image, this algorithm can reach 98.6% on identification rate, while the grid algorithm is 92.3%, and the pyramid algorithm is 87.2%.
Improved automatic exposure algorithm for the stereoscopic panoramic camera in space application
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The automatic exposure algorithms have been successfully used in a variety of imaging platforms. However, most automatic exposure algorithms are not suitable for the application in space due to the complicated space environment, such as dramatically varying temperature and special space background. Additionally, the algorithms must be designed to adapt to the hardware platform with the limited storage capacity and real-time capability. This paper proposes an improved automatic exposure algorithm for the special application scenario in space, which is suitable for the real-time application of space panorama cameras. In this paper, a simulation experiment of the mean-based exposure algorithm is carried out. And the result shows that temperature change and deep dark background in space environment will cause the computation error. So we introduce the iterative calculation and automatic threshold segmentation method to improve the mean-based exposure algorithm. The improved algorithm is implemented using FPGA in standard hardware description language (VHDL), and a test platform to simulating deep space environment is built with a halogen lamp, a whiteboard and a temperature controlled tank in a dark room. The experiment results show that the exposure time almost unchanged when the dark background varies greatly (25% ~ 100%), which verifies that the effect of dark background is removed. And it can be demonstrated that the influence of temperature on the algorithm is decreased, which based on the experiment result that the exposure time decreases with increasing temperature (15°C to 70°C).
Linear-mode linear arrays 16 pixel silicon avalanche photodiodes with high gain and low noise readout
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A hybrid integrated photodetector consisting of array of reach-through avalanche photodiodes and readout integrated circuit chips was developed. The reach-through avalanche photodiode model with separate layer of absorption, charge and multiplication are elaborated. This kind of photodiode is optimized for detection of 905 nm radiation and in that range achieve excellent parameters – high gain, low noise and high speed. Next, the design and properties of the readout integrated circuit with a new-type regulated cascode circuit configuration are discussed. The linear array reach-through avalanche photodiode and readout integrated circuit chips were integrated into a photodetector by using bonder-leading welding techniques. The integrated detector demonstrates the pulse responsivity R ≥ 1×106 V/W, the noise equivalent power NEP ≤ 5 pW/Hz1/2, and the rise time tr ≤ 3 ns, under pulsed laser irradiation at 905 nm, 100 ns and 10 KHz.
Influence of image sequence distortion on infrared target detection
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Because of the platform motion and system internal asymmetric structure, Satellite-borne infrared imaging system will generate image geometric distortions such as translation, rotation, distortion and scaling, which make the subsequent target detection result not accurate. Therefore, we propose an image distortion method and deeply analyze the influence of infrared image distortion on the SNR of infrared weak small targets, detection probability and false alarm probability. The simulation results show that the image distortion directly affects the subsequent performance of the infrared target detection and tracking algorithm by changing target geometric imaging and signal to noise ratio. The research result in this paper would have great application value in the satellite-borne infrared alarm/warning system.
Image restoration from sequences under atmospheric turbulence effects
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Turbulence makes the image suffer from geometric distortion, pixel deviation and blur. This paper focuses on image restoration under atmospheric turbulence. To improve the image quality, we revisit the problem by a two-phase method. According to the distortion model analysis, we first combine affine transformation with non-rigid registration to suppress global motion and local pixel deviation. To improve the registration speed, the cost function is optimized by L-BFGS algorithm. Next, a multi-frame blind deconvolution algorithm is employed to restore the registered frames, and get a final output. The experimental results clearly demonstrate the effectiveness of the proposed method. It can effectively alleviate blur and distortions, improve visual quality and recovery speed significantly.
Theoretical and experimental study on the block compressive imaging
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As compressive imaging can capture high-resolution images using low-resolution detectors, it has received extensive attention recently. Compared to Single-pixel Compressive imaging, block compressive imaging (BCI) can considerably reduce the observation and calculation time of the reconstruction process, therefore it can also reduce the speed of imaging. A common challenge in BCI implementation is system calibration. In this paper, we use system spread point function into object reconstruction process to solve this challenge. In our simulation works, a 64x64 object with block size 4x4 is used. 6 measurements are collected for each block. Orthogonal matching pursuit (OMP) algorithm is applied to reconstruction. Additionally, we setup an experiment to demonstrate BCI idea. The BCI experimental platform confirms that images at high spatial resolution can be successfully recovered from low-resolution sensor.
Comparison of non-scanning laser 3D imaging using Geiger-mode APD array and linear APD or APD array
Chunbo Liu,
Fang Bai,
Jingxiong Zhang,
et al.
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Some typical non-scanning 3D imaging systems using Geiger-mode APD array and single-pixel 3D imaging technique are first summarized, respectively; and the performance of two imaging mode is compared to from several aspects such as image resolution, imaging frame rate, and etc. Analysis of the key techniques of two imaging techniques is conducted and some advices for appropriate application scenario are made based on their features. Moreover, a trade-off 3D imaging scheme based on linear low-pixel APD array and correlated imaging is proposed. The analysis shows that the new scheme can decrease the time-sample requirement and further increase the imaging speed compared with traditional system, while avoiding the dependence on high-pixel APD array.
Study on calculating methods of forest fire area for dynamic disaster assessment based on infrared image
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According to the characteristics of forest fire spread fast, difficult to save, in order to determine the forest fire danger rating quickly and strive for fire time, it is important to calculate the fire area. Considering that there is a close relationship between the gray image of infrared image with temperature, the gray value of infrared image corresponds to high temperature object will be large. At the same time fire occurs, the temperature of the flame is generally higher than the temperature of the surrounding environment , infrared image can be used to exclude a lot of non-fire interference source and provides a simple and convenient criterion for the identification and segmentation of flame area, so this paper presents a calculation method of fire area based on infrared image. The method take full advantage of the significant characteristics of the obtained forest fire infrared image, the coordinate relationship between the image and the camera is established and the camera is calibrated. Then extract the edge of the forest fire spread, utilizing sobel operator rough location, and then grayscale image interpolation, cubic spline interpolation function so that the target to achieve sub-pixel level grayscale images after interpolation, the use of the maximum variance between the threshold is determined to achieve sub-pixel edge detection. The edge of the forest fire spread is extracted, with images used to calculate the forest fire burned area, with the error of measuring result calculated. The results show that the maximum error is controlled within 4.5%. Therefore, the forest fire area calculation methods can be applied to the fire control and post- disaster assessment of forest fire. The method is feasible and convenient calculation and will be of great significance to the forest-fire prevention.
Forest fire real-time monitoring and emergency treatment system design
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Combining forest fire monitoring system with fire extinguishing unmanned aerial vehicle (UAV) formation , a system design scheme for forest fire security and protection system is also presented in this paper, at the same time , this system combined with machine vision technology and GIS positioning system , and the fusion of multi-date information to guarantee the accurate and precise positioning of the fire events, etc . At the first, the fire information will be real-time processing by airborne imaging devices, then be transmitted to the control center and be analyzed , the fire area, the number of the required fire extinguishing UAV and UAV formation information will be calculated and the take-off command will be sent . During the UAV formation flight process, the geographic data and formation flight data of UAV will be transmitted in real time and the perceived wind speed data will be transmitted back to the control center when the UAV formation arrives at the scene of fire , then , after the correction of the date , the command of sending fire extinguishing material will be sent by control center to put out forest fires, ultimately avoid the fire spread, minimize losses, and enhance the security level of forest fire disaster lash-up processing capability. Therefore , this forest fire security system have a good application prospect.
The research for calibration technology of ultraviolet-vacuum ultraviolet imaging spectrometer
Guang-wei Sun,
Hong-sheng Sun,
Jia-peng Wang,
et al.
Show abstract
The application of ultraviolet-vacuum ultraviolet imaging spectrometer in space exploration is becoming widely, in its development process need calibration for imaging spectrometer, but there is still no measurement standard, can not guarantee the accuracy and reliability of test results. This paper presented a calibration device for ultraviolet-vacuum ultraviolet imaging spectrometer, realized calibration for spectral range, spectral accuracy degree, spectral response rate, space angle resolution, non-uniformity, and achieved good results.