This PDF file contains the front matter associated with SPIE Proceedings Volume 8200, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

An adaptive optics scanning laser ophthalmoscope (AO-SLO) using a liquid-crystal spatial light modulator was developed. For routine clinical applications, long-term stability of the AO system is very important because unavoidable eye movement may degrade the instrument's performance. We studied the long-term performance of the aberration correction with healthy human eyes. Retinal image acquisition and AO data collection were performed simultaneously for periods of several minutes. We confirmed that, for more than 90% of the periods, the root-mean-square errors of residual wavefront were below the Marechal criterion. Drifts and microsaccades of fixational eye movement were examined using retinal images and residual aberrations. The results showed significant correlation between the transverse shift of retinal image and the low-order residual wavefront aberration during the drifts.

We demonstrate tomographic imaging of intracellular activity of living cells by a low-coherent quantitative phase microscope. The intracellular organelles, such as the nucleus, nucleolus, and mitochondria, are moving around inside living cells, driven by the cellular physiological activity. In order to visualize the intracellular motility in a label-free manner we have developed a reflection-type quantitative phase microscope which employs the phase shifting interferometric technique with a low-coherent light source. The phase shifting interferometry enables us to quantitatively measure the intensity and phase of the optical field, and the low-coherence interferometry makes it possible to selectively probe a specific sectioning plane in the cell volume. The results quantitatively revealed the depth-resolved fluctuations of intracellular surfaces so that the plasma membrane and the membranes of intracellular organelles were independently measured. The transversal and the vertical spatial resolutions were 0.56 μm and 0.93 μm, respectively, and the mechanical sensitivity of the phase measurement was 1.2 nanometers. The mean-squared displacement was applied as a statistical tool to analyze the temporal fluctuation of the intracellular organelles. To the best of our knowledge, our system visualized depth-resolved intracellular organelles motion for the first time in sub-micrometer resolution without contrast agents.

This paper describes an experiment-based model to simulate 3D infrared target in sea background. The geometric model of dynamic sea waves are based on gravity wave theory, while the sky model use SkyDome technology which takes the sky as a dome covers the land. To create the infrared images of sea waves and sky, the radiance at the detector are calculated. To acquire the radiance of target radiation, a spectrometer is settled to measure the radiant emitted by interested targets. Meanwhile, the radiant of sky is also measured to provide reference data. Furthermore, the spectrometer is used to measure the atmospheric transmission rate which is compared to the values calculated by MODTRAN. The optical system is simulated based on OTF theory. The detector noise is expressed as an equivalent Gaussian white noise. Finally, the simulation images are compared with the practical images. It has been proved that this experiment-based model produces infrared images with high reality.

This paper introduces a novel method to adaptively diminish the effects of disturbance in the airborne camera shooting traffic video. Based on the moving vector of the tracked vehicle, a search area in the next frame is predicted, which is the area of interest (AOI) to the mean-shift method. Background color estimation is performed according to the previous tracking, which is used to judge whether there is possible disturbance in the predicted search area in the next frame. Without disturbance, the difference image of vehicle and background could be used as input features to the mean-shift algorithm; with disturbance, the histogram of colors in the predict area is calculated to find the most and second disturbing color. Experiments proved this method could diminish or eliminate the effects of homochromous disturbance and lead to more precise and more robust tracking.

Using thermal infrared imaging to obtain the temperature distribution of the train wheel sets is a new and promising temperature measurement method. The accuracy and precision of the method are suffered from vignetting. In this paper, the vignetting coefficient function has been derived and imaging system calibration is introduced to compensate the measurement result error caused by the inconsistent of the optic center and the image center. The vignetting correction is implemented on the hardware platform based on FPGA. Experimental results demonstrate that vignetting correction enhance the accuracy of measurement system.

Point target detection is an important issue for the application of infrared search and track (IRST) system. To detect the weak point target in infrared image, this paper introduces a new method based on two-steps gradient algorithm to eliminate the impact of complicated background and extract possible targets. Firstly, the characteristics of point target are analyzed based on 288x4 linear infrared FPAs. Secondly, the point targets in complicated infrared background are classified into four groups. The detection function is derived for each group, and then the comprehensive detection function is derived to extract the point target. Finally, a practical experiment is completed based on a 288x4 IRST system. It is proved that the two-steps gradient algorithm can reduce the number of possible targets which is helpful to the post-processing work.

A video laparo endoscopic system was introduced in this paper, which included a camera, a white LED illuminator and a high-definition image processing workstation. The camera adopted a CMOS image sensor to achieve high resolution imaging. Four LEDs were assembled directly to the front-end of the endoscope. Optical fiber coupling system was unnecessary. Image processing workstation was used to demosaic, enhance, and display the image on an LCD monitor in real time, and then capture and store the image. The image resolution reached 1280*1024. This system can be used directly in a laparoscope casing of 10mm in diameter. It is compact, low-cost, high-definition, and suitable for the single-port laparoscope surgery.

Wavefront coding technology can extend the depth of field of the iris imaging system, but the iris image obtained through the system is coded and blurred and can't be used for the recognition algorithm directly. The paper presents a fuzzy iris image restoration method used in the wavefront coding system. After the restoration, the images can be used for the following processing. Firstly, the wavefront coded imaging system is simulated and the optical parameter is analyzed, through the simulation we can get the system's point spread function (PSF). Secondly, using the blurred iris image and PSF to do a blind restoration to estimate a appropriate PSFe. Finally, based on the return value PSFe of PSF, applying the regularization filter on the blurred image. Experimental results show that the proposed method is simple and has fast processing speed. Compared with the traditional restoration algorithms of Wiener filtering and Lucy-Richardson filtering, the recovery image that got through the regularization filtering is the most similar with the original iris image.

Based on the spectrum rebuilding technology of spatially modulated imaging spectrometer, a real-time data gathering and spectrum rebuilding system of all reflection Fourier Transform imaging spectrometer is built on FPGA. It integrates interferogram sampling, spectrum rebuilding, data restoring, VGA display and data transmission on a single chip of FPGA and can make them accomplished in real-time. This paper presents the key technology and the spectral calibration study of this system. Using a mercury lamp as the calibration source, the calibration experiments have been carried on this FPGA-based system. After analysis the experimental results, a function of pixel number-wave number has been established, and the wave number resolution has been got, which is same to the resolution got by a computer-based system.

Currently, underwater divers become one of the main forces for underwater rescue and exploration. In order to extend the search distance of the underwater divers, miniaturized underwater optoelectronics imaging system turns out to be the main direction of development in and abroad. On the basis of introduction to some optoelectronic imaging advices for underwater divers, this paper designs a set of handheld underwater observation instruments used for underwater rescue and exploration, using the range-gated imaging technology, to eliminate the bad influence efficiently which is caused by the water backscatter. This paper gives some introductions about principles, system construction, and control system part, and makes a brief analysis of the characteristics and prospect of the system.

Here two imaging spectrometers, based on a different prism-grating-prism (PGP) dispersing component, are designed and presented. One works at the visible near infrared (VNIR) waveband from 400nm to 1000nm with 1.7nm/pixel spectral resolution, 85mm track length. As for the other, its spectral coverage, spectral resolution, and track length are the short wavelength infrared (SWIR) waveband from 900nm to 1700nm, 3nm/pixel, and 108mm, respectively. Both of the imaging spectrometers have advantages of fast speed (F/2.0), wide spectral range, low distortion, low cost, even relative illumination, and compactness made them ideally suited for hyperspectral imaging remote sensing. Either of them gains the preferable imaging quality.

Based on the wave aberration theory, a new method of optical design of the planate symmetric Offner type imaging spectrometer is performed. Astigmatism changing with the diffraction angle of the grating, the meridional and saggital focusing characters are all studied. Determination of the initial configurations and optimally design methods of two improved types of Offner imaging spectrometer are discussed in detailed. A design example with the numerical aperture larger than 0.2, and the entrance slit 30mm is given. Its spectral resolution is better than 2nm and MTF is above 0.7@20lp/mm. The smile and keystone are less than 3% and 0.2% of the pixel respectively.

Automatic peak detection is important for the application of Raman spectroscopy. However, the existence of noise and baseline disturbances will greatly degrade the reliability and accuracy of the peak detection. In this paper we proposed a hybrid wavelet-transform-based algorithm to improve the peak detection performance. Here, continuous wavelet transform method was used to robustly identify the spectral peaks, and to minimize the influence of noise and baseline disturbances. A localized curve-fitting method was used to obtain the accurate parameters of the peaks, such as location, width and intensity. The simulation and experiment proved that this method was robust against various disturbances and it could not only automatically detect the peaks but also obtain accurate parameters of the spectral peaks.

Registration of two three-dimensional (3-D) point sets is a fundamental problem of 3-D shape measurement and modeling pipeline. This paper investigates the automatic pair-wise method to register partially overlapped range images generated by self-developed fringe pattern profilometry (FPP) system. The method is based on the classic iterative closest point (ICP) algorithm but combined with several extensions to adapt to the experimental data. Firstly, the distance function for correspondence finding is modified to be the weighted linear combination of positions and Euclidean invariant features for improving the probability of convergence. In addition, outliers can be discarded through robust statistics and adaptive thresholding of weighted distances between corresponding point pairs. Both artificial and real data are used to test the proposed method. In the ideal noise-free conditions, the experimental results illustrate that it converges to the global minima. The experimental results also show that the proposed method increases the possibility of global convergence when deal with partially overlapped range images.

3D face recognition technique has gained much more attention recently, and it is widely used in security system, identification system, and access control system, etc. The core technique in 3D face recognition is to find out the corresponding points in different 3D face images. The classic partial Iterative Closest Point (ICP) method is iteratively align the two point sets based on repetitively calculate the closest points as the corresponding points in each iteration. After several iterations, the corresponding points can be obtained accurately. However, if two 3D face images with different scale are from the same person, the classic partial ICP does not work. In this paper we propose a modified partial Iterative Closest Point (ICP) method in which the scaling effect is considered to achieve 3D face recognition. We design a 3x3 diagonal matrix as the scale matrix in each iteration of the classic partial ICP. The probing face image which is multiplied by the scale matrix will keep the similar scale with the reference face image. Therefore, we can accurately determine the corresponding points even the scales of probing image and reference image are different. 3D face images in our experiments are acquired by a 3D data acquisition system based on Digital Fringe Projection Profilometry (DFPP). A 3D database consists of 30 group images, three images with the same scale, which are from the same person with different views, are included in each group. And in different groups, the scale of the 3 images may be different from other groups. The experiment results show that our proposed method can achieve 3D face recognition, especially in the case that the scales of probing image and referent image are different.

This paper presents an absolute phase calculation method from one composite RGB fringe pattern image by using Wavelet transform algorithm and the optimum fringe number selection. Three fringe patterns having optimum fringe numbers are projected simultaneously onto an object surface via the red, green and blue channels of a DLP (Digital Light Processing) projector. From a different viewpoint, a CCD camera captures the deformed fringe patterns with respect to the object shape to get a composite RGB image. After compensating for the crosstalk and chromatic aberration between color channels, three fringe patterns are extracted from the composite color image. Wavelet Transform algorithm is studied to calculate wrapped phase from one fringe pattern. Therefore, three wrapped maps are obtained from the three extracted fringe patterns. An absolute phase map is calculated pixel by pixel after applying the optimum three-fringe numbers selection method to the three obtained wrapped phase maps. Simulated and experimental data demonstrate the algorithm's validity of calculating the absolute phase and shape information. The proposed method can measure 3D shape information of moving objects since the system needs only one RGB fringe pattern image.

3D fringe projection measurement techniques are increasingly important in production for automation, quality control, reversal engineering, and biomedical engineering because of the advantages of non-contact operation, full-field acquisition and automatic data processing. With the advent of DLP (Digital Light Processing) projectors, digital fringe pattern projection techniques have been widely studied in academia and applied to industries. The experimental data from living profile of fringe patterns show that the obtained intensity has some fluctuation, which cause the calculated phase data inaccuracy. This paper presents one software method to eliminate the fluctuation between fringe patterns. Four-step phase-shifting algorithm is used to calculate the wrapped phase data, so four fringe pattern images having pi/2 shift in between need to be captured. Because of the fluctuation of intensity, the captured fringe patterns have an up or down shift among the four images. By considering the histogram of each fringe pattern, we present one compensation method to eliminate the fluctuation between fringe patterns. Simulated data are first tested by generating fringe patterns with fluctuation. Then experimental data from a 3D imaging system demonstrate the validity for calculating the phase and shape information with high accuracy. The results show that the proposed method eliminates the fluctuation between fringe pattern images to give accurate shape data information.

Compressed sensing or compressive sampling (CS) is a new framework for simultaneous data sampling and compression which was proposed by Candes, Donoho, and Tao several years ago. Ever since the advent of a single-pixel camera, one of the CS applications - compressive imaging (CI, also referred as feature-specific imaging) has aroused more interest of numerous researchers. However, it is still a challenging problem to choose a simple and efficient measurement matrix in such a hardware system, especially for large scale image. In this paper, we propose a new measurement matrix whose rows are the odd rows of N order Hadamard matrix and discuss the validity of the matrix theoretically. The advantage of the matrix is its universality and easy implementation in the optical domain owing to its integer-valued elements. In addition, we demonstrate the validity of the matrix through the reconstruction of natural images using Orthogonal Matching Pursuit (OMP) algorithm. Due to the limitation of the memory of the hardware system and personal computer which is used to simulate the process, it is impossible to create such a large matrix that is used to conduct large scale images. In order to solve the problem, the block-wise notion is introduced to conduct large scale images and the experiments results present the validity of this method.

The developed spaceborne camera is an exclusive functional load of a micro satellite. The signal-to-noise ratio (SNR) reflects its radiance response and is the parameter that directly associates with the quality of its acquired images. The SNR determination task of the spaceborne camera mainly consists of two parts: As is reported before firstly the spatial environment is simulated and the atmosphere transmission mode is built with MODTRAN to calculate and predict the SNR of the speceborne camera under aerial working condition. In this paper, the in-lab measuring experiment is carried out to measure the theoretical imaging performance of the camera before its aerial use. An integrating sphere is utilized to supply well-proportioned illumination, and a number of images are acquired by the spaceborne camera under different luminance conditions. The images are processed in use of certain algorithm and a special filter to extract the noise. The SNRs corresponding to different illumination conditions are calculated so that full-scale radiance response feature of the camera can be gained. The dynamic range is another parameter that characterizes the imaging capacity of a camera. The relationship between dynamic range and SNR of a camera is to be explored in this paper. Different dynamic configurations are set and the SNRs of different dynamic range configurations are tested, which experimentally reveals the dynamic range's influence on SNR.

Phase calculation-based 3D imaging systems have been widely studied because of the advantages of non-contact operation, full-field, fast acquisition and automatic data processing. A vital step is calibration, which builds up the relationship between phase map and range image. The existing calibration methods are complicated because of using a precise translating stage or a 3D gauge block. Recently, we presented a simple method to convert phase into depth data by using a polynomial function and a plate having discrete markers on the surface with known distance in between. However, the initial position of all the markers needs to be determined manually and the X, Y coordinates are not calibrated. This paper presents a complete calibration method of phase calculation-based 3D imaging systems by using a plate having discrete markers on the surface with known distance in between. The absolute phase of each pixel can be calculated by projecting fringe pattern onto the plate. Each marker position can be determined by an automatic extraction algorithm, so the relative depth of each pixel to a chosen reference plane can be obtained. Therefore, coefficient set of the polynomial function for each pixel are determined by using the obtained absolute phase and depth data. In the meanwhile, pixel positions and the X, Y coordinates can be established by the parameters of the CCD camera. Experimental results and performance evaluation show that the proposed calibration method can easily build up the relationship between absolute phase map and range image in a simple way.

As a kind of photogrammetric platform unmanned aerial vehicles (UAVs) usually employ amateur digital cameras, the photogrammetric data availability depend on the integrated sensors calibration result and the flight performance, which are great limitations to the UAV systems used in aerial photogrammetry. In this work, a specific workflow for the UAV system calibration in survey field is introduced, first a calibration field built in the survey region by using artificial targets as ground control points, furthermore, a specific flight planning is developed, then we take a fix-wing UAV to implement the survey work. The results for the bundle adjustment are less than 0.5m. which is better than estimated the camera interior orientation parameters(IOP) in the lab. Also the study described which source of errors influenced the UAV photogrammetry and bring forward improvement advice.

In this paper, we describe a new design of semi-active laser guided decoding system based on FPGA. The system is designed to receive the echo pulse through a 4-qundrant laser sensor and process the digital laser pulses through analogdigital conversion, which are some fixed interval encoding signal reflected from the target. The decoding system improve the adjustment accuracy of the laser seeker, which reach 0.1us about 50 times in theory compared to current technology. State machine is used to address complicated laser signal, including how to hand of the identification and trapping of the correct laser pulses, how to hand of a state of anti-jamming, how to hand of capturing the laser pulses again after signal missing. And a real-time gate signal is adopted to enhance the ability of anti-interference[1]. Processed signal is used to monitor and control, the processed result is transmitted to a electric actuator and subsequently be sent to laser seeker as a guidance signal or to a PC to simulate and monitor or to be stored in Flash that can extract whenever needed. The whole performance of the system is oprated in laboratory and decoding model is simulated with Modelsim module in detail. The testing results show that the design can reduce the span of decoding time effectively, identify and track the echo pulses from target correctly even to the missed codes or interferential codes. The feasible technique wins the time for laser guidance, and has some theoretical and military value.

With the rapid development of the electronic technology, multimedia technology and mobile communication technology, video monitoring system is going to the embedded, digital and wireless direction. In this paper, a solution of wireless video monitoring system based on WCDMA is proposed. This solution makes full use of the advantages of 3G, which have Extensive coverage network and wide bandwidth. It can capture the video streaming from the chip's video port, real-time encode the image data by the high speed DSP, and have enough bandwidth to transmit the monitoring image through WCDMA wireless network. The experiments demonstrate that the system has the advantages of high stability, good image quality, good transmission performance, and in addition, the system has been widely used, not be restricted by geographical position since it adopts wireless transmission. So, it is suitable used in sparsely populated, harsh environment scenario.

The method to evaluate the grade of the pork based on hyperspectral imaging techniques was studied. Principal component analysis (PCA) was performed on the hyperspectral image data to extract the principal components which were used as the inputs of the evaluation model. By comparing the different discriminating rates in the calibration set and the validation set under different information, the choice of the components can be optimized. Experimental results showed that the classification evaluation model was the optimal when the principal of component (PC) of spectra was 3, while the corresponding discriminating rate was 89.1% in the calibration set and 84.9% in the validation set. It was also good when the PC of images was 9, while the corresponding discriminating rate was 97.2% in the calibration set and 91.1% in the validation set. The evaluation model based on both information of spectra and images was built, in which the corresponding PCs of spectra and images were used as the inputs. This model performed very well in grade classification evaluation, and the discriminating rates of calibration set and validation set were 99.5% and 92.7%, respectively, which were better than the two evaluation models based on single information of spectra or images.

Stripe images of electronic speckle shearography pattern interferometry, in which stripe distribution are correlated with vertical micro distortion or micro vibration of objects, are severely disturbed by noises, and so denoising stripe images of electronic speckle shearography pattern interferometry is necessary to extract useful stripe distribution information. Denoising methods and flow for stripe images of electronic speckle shearography pattern interferometry are analyzed in this paper to get the stripe distribution correlated with vertical micro distortion or micro vibration of objects. The noises in the stripe images of electronic speckle shearography pattern interferometry are comprised of speckle noise and other random noises induced by environmental disturb and instrumental performance, so it's difficult to use familiar filters, such as mean-value filter, medium-value filter and adaptive filter, etc, to remove all noises in the stripe images. The combined filter composed of mean-value filter and wavelet filter is designed to denoise stripe images. The aim of mean-value filter is to remove random noises induced by environmental disturb and instrumental performance, and then the wavelet filter, in which the Meyer wavelet is adopted, is designed to remove speckle noise in the stripe images. The final stripe distribution images after denoising and binarization are listed to prove the denoising validity of combined filter based on wavelet transform.

This paper proposes a novel algorithm for distinguishing scenery information from cloud noise in the low-level and high-level detail coefficients using the wavelet decomposition. Also this paper shows approximate coefficients only containing the scenery information, and high-level detail coefficients mainly including the cloud noise and the partial scenery information. Usually cloud is brighter than the scene illumination. Therefore the appropriate brightness threshold is setup for processing high-level detail coefficients aimed at the elimination of cloud noise. Simultaneously to remove the residual cloud at the low frequency component and improve the clarity of the scenery image, the paper further decomposes the detail coefficients based on the frequency. For example, the low-level detail coefficients are decomposed further once or twice by wavelet packets. So we can remove remaining cloud decomposed effectively at the low frequency, and through assigning the appropriate weight to the detail coefficient, achieve the goal for enhancing scenery information and improving the image clarity. Considering influence of the parameter changes on the algorithm performance, we use the entropy as the criterion for choosing the optimal parameters step by step. We have demonstrated that this algorithm using the entropy as criterion is feasible. The experimental results are superior to homomorphism filtering and the Retinex algorithm in many aspects.

In order to improve the image contrast and strengthen the details of high dynamic range (HDR) infrared (IR) image, a detail enhancement method based on histogram statistical stretching (HSS) and gradient filtering (GF) is proposed. First, the outliers in the HDR image are clipped by the proposed histogram statistical strategy and the clipped histogram is then extended to a new grayscale range to acquire a better contrast of view. The details in the HDR image are extracted by using the GF and its result is then adjusted by using the HSS to enhance the low-contrast detail perception. Finally, the GF result is superposed with the HSS result in a proper way to generate the final detail-enhanced image. The contribution and innovation made is threefold. A new technique for visualization of HDR image especially tailored to IR image is proposed. The effectiveness and convenience are shown by analyzing the experimental images that represent the typical and common IR scenes. Last, the performance is quantitatively assessed compared with other well-established methods. The simulation and experimental results approve its low cost, low complexity and promising outlook for real-time processing.

A large number of stars in the drift-scanning star image have interfered with the detection of small target, this paper proposes an adaptive linear filtering method to achieve the small target detection by suppressing the stars. Firstly, the characteristics of stars, interest target and noise three different representative objects in the star image are analyzed, then the standardized linear filter is constructed to suppress the stars. For the purpose of decreasing the influence region of stars filtering uniformly, a gradient linear filter is constructed to modify the stars suppression method with the standardized linear filter. Then the filter parameter selection method is given. Finally, a multi-frame target track experiment on the real drift-scanning data is made to testify the validity of the proposed method. With the processing results of different methods, it has been showed that the proposed method for suppressing stars with different length and lean angle has a better effect, higher robustness and easier application than the others.

The contrast enhancement of infrared image is useful and important to the infrared image system. The current techniques of local enhancing exists either over-enhancing or high complexity problems. In this paper, we propose a novel contrast enhancement algorithm which combines histogram equalization based methods (HEBM) and an improved unsharp masking based methods (UMBM). This proposed algorithm uses HEBM to achieve global contrast enhancement and UMBM to achieve local contrast enhancement. Some elaborate strategies are applied to the algorithm to avoid the overenhancement and magnification of noise when contrast is enhanced. The article is organized as follows. First, we review the techniques developed in the literature for contrast enhancement. After then, we introduce the new algorithm in details. The performance of the proposed method is studied on experimental IR data and compared with those yielded by two well established algorithms. The developed algorithm has good performance in global contrast and local contrast enhancement with noise and artifact suppression.

We present a method of target detection against strong light based on gate viewing. In this method, a nanosecond-scale gate shutter is used to control the exposure time of CCD and reduce the collection of obtrusive light, and a nanosecond-scale pulsed laser is used to illuminate targets and increase signal energy. By matching them, the ratio between signal and obtrusive light will be significantly improved to detect targets against light disturbance. We have analyzed the method in theory, and performed it in experiment. In addition, a stroboscopic time sequence is used, and the setting of temporal parameters is also discussed.

Based on the theory of the coherent detection of laser, a signal model of Synthetic Aperture Lidar is set up. As the wavelength of laser light from the SAL is shorter than that of microwave from the SAR about several times, considering the parts of Taylor Series must be enough, compute and analysis the influence of vibration error on the phase of SAL echo signal. In order to validate the signal model and the theory computation, numerical simulation on a strip-mode is carried out. On the reference of the national military standard for environment, in the condition of the frequency below 500MHz, simulate and show the influence of the vibration parameters such as amplitude, frequency or initial phase on the SAL imaging, and the image with the vibration of ideal point target is given. The simulation results show that the influence of vibration on the azimuth resolution is severity, but that on the range resolution is trivial, this is by the reason of the period of vibration is different from the period of laser pulse, and in one laser pulse period, the vibration is considered immovability, therefore the influence on the range compress is nonentity, and the range resolution is steady. In addition, simulate the condition of the same amplitude and frequency but different initial phase, find that the influence of different initial phase on SAL imaging is different and serious, as the initial phase is stochastic, the influence of vibration on SAL imaging is erratically.

How to simulate the decay pattern is crucial during lifetime inversion while utilizing intensity images acquired at increasing delays in time gated fluorescence lifetime imaging microscopy (FLIM) method. A relatively novel understanding of fluorescence decay pattern theory and stimulation algorithms of time gated FLIM method have been analyzed in this paper comprehensively. Main lifetime computing algorithms can be classified as exponential pattern retrieve and polynomial fitting procedure. Especially, a novel lifetime computing method based on bi-exponential decay has been discussed. In experiment, we have validated the proposed algorithms utilizing synthetic images. Performances like calculating precision and computing speed of the algorithms above have also been compared.

High speed railway develops rapidly in recent years in China. Wheel set is the major running components of a train. Online measurement of wheel set wear parameters is important for the train safety. A method of wheel sets' wear online measurement based on structure light imaging and image analysis was proposed. A new image segmentation algorithm of wheel set based on region growing was put forward based on characteristics of wheel set images. According to the characteristics of wheel set images acquired in different circumstance, proper seed and appropriate growth standard was determined. After growth processing, the whole tread profile images were extracted. By processing number of images, the proposed algorithm eliminated effectively the interferences in the image acquisition and extracted whole wheel set profile curve from varied background.

Eye-safety analysis is very important in the civil application of infrared laser imaging. In order to meet the requirements of human eye-safety protection, a model of eye-safety analysis is established based on ANSI Z136.1 Standard. When the value of maximum permissible exposure is given, one can estimate laser power and beam divergence angle under desired eye-safety distances from the model. We have simulated the model by MATLAB and given the laser power curve at different distances. Based on the curve, the eye-safety parameters of laser imaging systems can be easily designed. Therefore, the proposed model of eye-safety analysis can help to standardize infrared laser imaging products.

Recent years, the MEMS-based optical readout infrared imaging technology is becoming a research hotspot. Studies show that the MEMS-based optical readout infrared imager features a high frame rate. Considering the high data Throughput and computing complexity of denoising algorithm It's difficult to ensure real-time of the image processing. In order to improve processing speed and achieve real-time, we conducted a study of denoising algorithm based on parallel computing using FPGA (Field Programmable Gate Array). In the paper, we analyze the imaging characteristics of MEMS-based optical readout infrared imager and design parallel computing methods for real-time denoising using the hardware description language. The experiment shows that the parallel computing denoising algorithm can improve infrared image processing speed to meet real-time requirement.

Laser image often contains mixed noise mainly including salt and pepper noise and Gaussian noise. Not only the quality of laser image is made deteriorated but also the important details of laser image are flooded by it. A new mixed noise filtering method for laser image is proposed in this paper to filter out mixed noise effectively meanwhile ensure laser image details clear and completed. In the first space, salt and pepper noise in laser image is filtered out in spatial domain. A Novel Adaptive Switching Median (NASM) filter based on local salt and pepper noise density which determines filter window of every salt and pepper noise point adaptively is introduced here. Secondly, image is transferred to wavelet domain to filter out Gaussian noise. Local Adaptive BayesShrink Threshold (LABT) wavelet denoising on basis of Gaussian Mixture Model (GMM) is used in this step where wavelet coefficients are modeled by GMM and LABT is used for adjusting the threshold adaptively which utilizes local relevant characters of sub band wavelet coefficients. Experimental results show that new method can remove mixed noise effectively meanwhile protect details of laser image well thus getting better filtering performance compared with other filters for laser image.

The research on the mix blurred images restoration of defocus and motion were scarcity nowadays but these images were familiar in the actual work much more. Characteristics of the combined PSF which introduced the blur were investigated thoroughly based on the research of defocus blur and motion blur separately anciently. Defocus radius could be calculated by using the autocorrelation of the derivative image; motion angle could be captured by Radon translation and motion blurred extent could be computed by correlation alone the angle. Then the restoration could be developed using MPMAP Super-Resolution algorism with these three parameters. Validity of this method had been proved by the simulated mix blurred image and actual ones. This method would be used in the actual work after optimization in the future.

Motion blurred images could be restored by Super-Resolution arithmetic which took the angle calculated by Radon transformation of the spectrum of original images and the extent calculated by autocorrelation as parameters necessarily even though the blur of images was very severity. Unfortunately the noise of blurred images would be amplified while we captured useful information, which influenced the observation of restored images seriously. An enhancement arithmetic was proposed in this discourse to improve the quality of the low signal-noise ratio images obtained through restoration arithmetic. The main purpose of the arithmetic was to eliminate unwanted noises and remain desired signals. The arithmetic was based on the principle of the least square error method, which fitted discrete pixels to continuous piecewise curves. The interval of each row and column was subdivided into several subintervals to predigest the fitting of pixels. Then a curve was used to fit the pixels within the subinterval. A weighting technique with a linear weighting factor was proposed to merge two adjacent lines together. A series of experiments were carried out to research the effects of the arithmetic, and the signal-noise ratio showed that the proposed arithmetic could achieve high quality enhancement images.

This paper presents a novel method of 3D shape measurements of specular surfaces, based on fringe reflection technique and Fourier transform profilometry. A simple measurement system is set up. In this system, an LCD screen is used to display orthogonal composite fringe patterns. The fringe patterns reflected by a standard plane mirror and a measured specular surface are captured by a CCD camera. The phase distributions of the fringe patterns would be extracted by using Fourier transform profilometry. Relations between the surface gradients and phase changes in horizontal and vertical directions have been established. Then the shape of the measured surface can be reconstructed from gradient vector field by full-field least square method. The experiment of a concave mirror with a 100-mm diameter proves the validity of this method.

Lidar reflective tomography imaging has been shown a technology to obtain high resolution image of remote object, and has great application value in the field of space object surveillance and identification. In this paper, the fundamental of lidar reflective tomography imaging is given, some key issues of ground-based lidar reflective tomography imaging of space object are analyzed: the long-range detection and high range resolution is obtained by using chirp transmit signals, the usefulness of these range data for use in reflective topographic reconstruction of space object image is discussed; atmospheric turbulence effects on the reflective tomography is analyzed, which shows that 10.6μm lidar reflective tomography is not sensitive to atmospheric turbulence under certain receiving aperture; in order to resolve the question of incomplete detection angles in space target reflective tomography, regularization method is applied, the homotopy parameter is adopted in order to fix the weight coefficient efficiently, accuracy of image reconstruction has been improved. At last, the simulation results of satellite model validate the feasibility of this technical scheme.

Optic fiber coils are the hearts of fiber optic gyroscopes (FOGs). To detect the irresistible errors during the process of winding of optical fibers, such as gaps, climbs and partial rises between fibers, when fiber optic winding machines are operated, and to enable fully automated winding, we researched and designed this vision-based error detection system for optic fiber winding, on the basis of digital image collection and process[1]. When a Fiber-optic winding machine is operated, background light is used as illumination system to strength the contrast of images between fibers and background. Then microscope and CCD as imaging system and image collecting system are used to receive the analog images of fibers. After that analog images are shifted into digital imagines, which can be processed and analyzed by computers. Canny edge detection and a contour-tracing algorithm are used as the main image processing method. The distances between the fiber peaks were then measured and compared with the desired values. If these values fall outside of a predetermined tolerance zone, an error is detected and classified either as a gap, climb or rise. we used OpenCV and MATLAB database as basic function library and used VC++6.0 as the platform to show the results. The test results showed that the system was useful, and the edge detection and contour-tracing algorithm were effective, because of the high rate of accuracy. At the same time, the results of error detection are correct.

We describe a high-speed, high-resolution, and real-time scanning measurement system consisting of a linear laser, a smart camera, a PC and the corresponding software. The smart camera with high-speed processing capability could process the image of the object to be measured which is illuminated by the laser to get the data about the shape of the object's cross-section profile in real time. We just need to transport the measured data rather than the huge number of original image to PC for archiving or other application. By the relative motion between the system and the object, we can get a series of data about the whole object's profile which can be reconstructed in the PC by corresponding application software. The system was designed to be installed on the vehicles. With the moving of the vehicle we can get the shape of the road.

A color image segmentation algorithm which integrates watershed with automatic seeded region growing and merging is proposed in the paper. Firstly, the image was transformed from RGB color space to HSI space. Next, watershed algorithm was applied to the image to obtain initial segmentation effect. And then, Based on the results of watershed segmentation, some regions in the image were selected as seeded regions automatically for seeds growth algorithm by making use of color differences and relative Euclidean distance. Finally, a region combining algorithm was executed to avoid excessive segmentation. The proposed method combines the advantages of watershed and region growing approach, and in accord with the human vision segmentation strategy. This algorithm was applied to segment some images, the experimental results confirm its effectiveness and efficiency.

Using high-speed visual equipment is an effective method to locate mobile targets. Under the circumstance of high sensitivity(500Hz), except for the Gaussian noise, atmospheric instability has also an important impact on the image quality. To solve the problem, a method is proposed in this paper based on image power spectrum to analyze and evaluate the Gaussian noise, atmospheric noise meanwhile combined with wavelet denoising to remove the noise aiming at the images acquired by DALSA's 8192*32 high-sensitivity camera. Firstly, image databases are established based on the outdoor working conditions, including normal images, Gaussian noise images loaded with different simulated characteristics and atmospheric noise images in different simulated frequencies. Power spectrum ratio of all the images in the databases is calculated, and the image power spectrum critical value is determined. Then the evaluation and classification of the image noise is got according to the databases and the threshold. wavelet denoising is introduced to remove the noise subsequently. Finally, the comparison of power spectrum between the image untreated and treated is made to evaluate the effect of the method above. Experimental results show that the way can evaluate and remove the noise of image effectively for high-speed visual images.

Sun is used as light source for spectrum analysis of atmosphere material with light through atmosphere. The stronger sunlight enters the detector, the more accuracy can be achieved. However, due to the inhomogeneity of the atmosphere, the gray image of sun is not only irregular, even the interference of clouds will divide sun into different parts. A novel method for gray centroid of sunlight based on image recognition is presented. This method aiming at accurately obtaining the strongest sunlight through the atmosphere for detector uses the gray image of sun to calculate the actual gray centroid of sunlight.

BRDF (Bidirectional Reflective Distribution Function)is broadly used in many fields, such as physics, heat transformation, remote sensing, and computer graphics. Traditional methods to measure BRDF are expensive for most peoples, and image based approach becomes a novel direction. Until now, for such an image based system, at least a video camera and a still camera are indispensible, and the operations are not easily carried out under a convenient condition. In this paper, a method using only one still camera is proposed, with the help of a light source, a cylinder support, and a sphere. The material to be measured is painted on the sphere, putting on the cylinder support painted with BRDF- known material. Around the cylinder support, a simple control points nets are distributed. In the measurement process, the light source and the support are fixed, operators goes around the sphere to obtain pictures at different view angles and the rest work is finished automatically by a set of programs. The pictures are first processed by a photogrammetric program to get the geometry in the scene, including the positions, directions, and the shapes of light source, the support, the sphere, and the cameras. The BRDF samples are calculated from the image intensity and the obtained geometric relations, which are approximated by a multivariable spline to get a full BRDF description. Three different materials are tested with the method.

Fused-taper optical fiber devices are the most typical and basic optical passive devices. Electro-thermal fiber welding and tapering technique is one of new optical fiber fusion welding technologies and the heater's shape and temperature distribution has an important influence on the quality of optical fiber fusion. With help of Finite Element Analysis software, the temperature field distribution character of the specially shaped heater and surrounding temperature field are analyzed. According to the different kinds of microstructure optical fiber, adjust electrical parameter timely, then, better quality of optical fiber fusion will be got. In the paper, it suggests a vision measurement on the specially shaped heater's surface parameter which is based on image processing technology. This method chooses CCD as the image sensor. Firstly, median-filter of the 3x3 window in the detecting system is chosen to do the image pretreatment. Secondly, canny operator whose anti-noise capacity is strong is chosen as the edge detection operator in the system. Thirdly, with the method of least square, subarea curve fitting and straight line fitting are done to specially shaped component. The experiment results show that the morphology parameters of specially shaped heater can be calculated accurately. And the parameters can provide important information for studying on the heater temperature field distribution and the performance of the optical fiber fusion welding technology.

This paper has studied a measurement method of geometric parameters of fiber which is ellipse twin-core fiber based on machine vision. Firstly, testing system does grey histogram of fiber end image and does binary image to extract cladding and air holes and then obtains coordinates of radius and center of cladding and air holes through Hough transform. Secondly, it obtains a image of two ellipse cores by increasing threshold and making fiber end binary, extracts contour of two ellipse cores applying edge chain code method, and then calculates coordinates of semi-minor axis, semi-major axis and center of two ellipse cores by using least squares fitting. The measuring accuracy of the method achieves 1 μm, it can meet the requirement of performance test and analysis of this microstructure fiber.

It will be a great convenience to compress images on a high proportion with the retention of details for transfering, storing, and processing images. In view of that, a new pretreatment technique - wavelet coefficients partition (WCP) algorithm was presented in this paper, which can subdivide the wavelet decomposing high frequency coefficient into high-frequency information and low-frequency information by setting threshold and iterative calculation. The low-frequency information can be compressed by 9/7 wavelet based on the promotion way. On the other hand, the detail information of the high frequency can be processed by the second generation Bandelet. Meanwhile, the specific optimization algorithm was also given in this article, through which the calculation can be reduced by three-quarters; and comparing with the original image, the PSNR value of the same bit rate decompressed image can be improved to the maximum of 10 db, the SSIM value tends to be 1. The experimental results show that the compression method is easy to run, and the visual effect of the restoring image is better than any of those that have been compressed by wavelet transform, JEPG2000, Bandelets and other conventional methods.

In this paper, a structure tensor based approach is proposed for multi-focus image fusion within the wavelet framework. Structure tensor is employed to extract local features in detail sub-bands. A nonlinear flow based on the trace of the structure tensor matrix is applied to matrix element before calculating the eigenvalues. The source data with larger eigenvalue contains more geometric features. An adaptive weight function is constructed to yield new detail coefficients of the fused image. Experimental results show that the proposed scheme improves performance compared to some related wavelet approaches.

Multiple targets tracking technology in infrared image is the core of multi-sensors information fusion. As to the features of infrared imaging and the difficulties in multi-target tracking, a kind of multi-target tracking in infrared image based on joint probabilistic data association (JPDA) algorithm is proposed in this paper. Detection algorithm is applied in infrared images to gain the initial information and observation information of targets. Designed tracking thresholds and set up the tracking beginning. Calculate the probabilities of measurements in track gate associated with target tracks, the probability is used to produce a weight innovation of measurements which is used to a target state estimating filter, complete the target track predict and filter update. Theoretical analyses and experimental results prove that the algorithm in the paper can be used to solve the distribution problem of multi-observation and multi-target tracks. Even two targets with cross bonding or overlapping can be stably and effectively tracked and remove the clutter from detection.

Binocular vision is one of the key technology in three-dimensional reconstructed of scene of three-dimensional machine vision. Important information of three-dimensional image could be acquired by binocular vision. When use it, we first get two or more pictures by camera, then we could get three-dimensional imformation included in these pictures by geometry and other relationship. In order to measurement accuracy of image acquisition system improved, image acquisition system of binocular vision about scene three-dimensional reconstruction is studyed in this article. Base on parallax principle and human eye binocular imaging, image acquired system between double optical path and double CCD mothd is comed up with. Experiment could obtain the best angle of double optical path optical axis and the best operating distance of double optical path. Then, through the bset angle of optical axis of double optical path and the best operating distance of double optical path, the centre distance of double CCD could be made sure. The two images of the same scene with different viewpoints is shoot by double CCD. This two images could establish well foundation for three-dimensional reconstructed of image processing in the later period. Through the experimental data shows the rationality of this method.

The paper presents a novel region merging method based on the interactive information from users. An image firstly is partitioned into homogeneous regions by using an initial segmentation and the regions will be label by taking an interactive scheme. In this scheme, the users only roughly specify the position and main features of the object and background, then any region will belong to non-label region or label region i.e. object or background. A similarity rule is used to guide the merging process with the help of the users' markers. And then the object of interest is extracted from the image. Experiment results show that the proposed method is efficient for us to extract the object of interest from the complex background.

Sweat pores and other level 3 features have been proven to provide more discriminatory information about fingerprint characteristics, which is useful for personal identification especially in law enforcement applications. With the advent of high resolution (≥1000 ppi) fingerprint scanning equipment, sweat pores are attracting increasing attention in automatic fingerprint identification system (AFIS), where the extraction of pores is a critical step. This paper presents a scale parameter-estimating method in filtering-based pore extraction procedure. Pores are manually extracted from a 1000 ppi grey-level fingerprint image. The size and orientation of each detected pore are extracted together with local ridge width and orientation. The quantitative relation between the pore parameters (size and orientation) and local image parameters (ridge width and orientation) is statistically obtained. The pores are extracted by filtering fingerprint image with the new pore model, whose parameters are determined by local image parameters and the statistically established relation. Experiments conducted on high resolution fingerprints indicate that the new pore model gives good performance in pore extraction.

During optical remote sensing imaging procedure, the relative motion between the sensor and the target may corrupt image quality seriously. The precondition of restoring the degraded image is to estimate point spread function (PSF) of the imaging system as precisely as possible. Because of the complexity of the degradation process, the transfer function of the degraded system is often completely or partly unclear, which makes it quite difficult to identify the analytic model of PSF precisely. Inspired by the similarity between the quantum process and imaging process in the probability and statistics fields, one reformed multilayer quantum neural network (QNN) is proposed to estimate PSF of the degraded imaging system. Different from the conventional artificial neural network (ANN), an improved quantum neuron model is used in the hidden layer instead, which introduces a 2-bit controlled NOT quantum gate to control output and 4 texture and edge features as the input vectors. The supervised back-propagation learning rule is adopted to train network based on training sets from the historical images. Test results show that this method owns excellent features of high precision, fast convergence and strong generalization ability.

An algorithm of sequence arrangement of wavelet transform (SAWT) for infrared focal-plane arrays (IRFPA) nonuniformity correction (NUC) aiming to remote sensing image was proposed. Firstly, distribution characteristics of pixel sequence of remote sensing image sequence were analyzed in wavelet space and scale space. Secondly, a reconstruction algorithm using mean value of approximation sequence arrangement of wavelet transform for NUC was proposed. Finally, nonuniformity of real infrared image sequence was correct by SAWT, and correction effect by SAWT compared with the algorithms of Kalman filter and Wiener filter. Results show that visual effect of SAWT is better than the other two algorithms with image sequence data quantity reduction, and the residual nonuniformity of sum image of sequence is 7-9 orders of magnitude lower than the other two algorithms, and the roughness of uniform area of image is less 0.0158-0.0544 than other algorithms. SAWT is also effective for NUC in IRFPA in less data quantity.

According to the abnormal spectrum produced by Oil micro-leakage in China's Gobi and sparse vegetated region, six types of spectrum data, which were used as the reference spectrum, were established for the database of exploring oil and gas. The USGS and JPL spectrum data, the spectrum data of alteration mineral in the gas field, the carbonation and clay mineral spectrum data and the hyperspectral spectrum data were contained in the database. The spectral characteristic information was extracted and integrated into the database. A series of interfaces were provided to users to allow the users to add their own spectrum features of the oil and gas areas, which will enhance the scalability of the feature database. The typical altered mineral spectrums produced by oil micro-leakage in China's Gobi and sparse vegetated regions were comprehensively covered in the database, which will enrich China's spectral library and is with the guidance of the oil and gas exploration by aerospace and aviation hyperspectral remote sensing.