This study evaluates the effects of beacon anisochromatatism on phase-compensation performance. In general, beacon anisochromatatism occurs at the system level because the beacon-illuminator laser (BIL) and high-energy laser (HEL) are often at different wavelengths. Such is the case, for example, when using an aperture sharing element to isolate the beam-control sensor suite from the blinding nature of the HEL. With that said, this study uses the WavePlex toolbox in MATLAB to model ideal spherical wave propagation through various atmospheric turbulence conditions. In order to quantify phase-compensation performance, we also model a nominal adaptive-optics (AO) system. We achieve low-order correction from a centroid tracker and fast-steering mirror and higher-order correction from a Shack-Hartmann wavefront sensor and continuous-face-sheet deformable mirror using least-squares phase reconstruction in the Fried geometry. To this end, we plot the normalized power in the bucket as a function of BILL-HEL wavelength difference. Our initial results show that positive BILL-HEL wavelength differences achieve better phase compensation performance compared to negative BIL-HEL wavelength differences (i.e., red BILs outperform blue BILs). This outcome is consistent with past results.

For small satellite remote sensing missions, a large aperture telescope more than 400mm is required to realize less than 1m GSD observations. However, it is difficult or expensive to realize the large aperture telescope using monolithic primary mirror with high surface accuracy. A segmented mirror telescope should be studied especially for small satellite missions. We propose the control algorithm of the deformable mirror for a segmented mirror telescope by using of observed image. The experimental results show that misalignment and wavefront aberration of the segmented mirror telescope are corrected and image quality is improved.

The effects of distributed-volume or “deep” turbulence in long range imaging applications presents unique challenges to properly measure and correct for aberrations incurred along the atmospheric path. Digital holography can detect the volumetric wavefront distortions caused by deep-turbulence to resolve the aberrations. Different recording geometries of the hologram offer different benefits depending on the application and previous studies have evaluated the performance off-axis and image plane recording geometries for wavefront sensing. This study models digital holographic detection in the phase-shifting recording geometry in the presence of deep-turbulence using wave optics simulations. In particular, the analysis models spherical-wave propagation through varying deep-turbulence conditions to estimate phase screens along the horizontal propagation path and the performance is evaluated by calculating the field-estimated Strehl ratio. Altogether, the results show digital-holographic detection in the phase-shifting recording geometry is an effective wavefront sensing method in the presence of deep turbulence.

The Shack-Hartmann Electron Densitometer (SHED) is a novel method to diagnose ultrashort pulse laser–produced plasmas by measuring the phase change to a probe laser beam. Using the Shack-Hartmann method, the phasefront of a probe laser is measured through a lenslet array onto a camera wherein small changes in the location of the focal points are translated into changes in the probe beam’s wavefront caused by the free electrons. By using SHED in a pump/probe setup, we are able to record synchronized, 2-D single shot measurements of free electrons in laser-induced ionization of air and other transparent media.

This abstract presents results from simultaneous measurements of density and wavefront distortions performed in a sonic underexpanded compressible flow jet. The density measurements are performed using Rayleigh scattering (RS), and the optical distortions are measured using a wavefront sensor. The underexpanded jet is surrounded by a low speed jet in a co-flow arrangement thus minimizing the presence of dust in the entrained flow. The simultaneous measurements of planar density and wavefront distortions should help in relating the effect of flow structure on optical degradation.

The turbulent effect from the Earth’s atmosphere degrades the performance of an optical imaging system. Many studies have been conducted in the study of beam propagation in a turbulent medium. Horizontal beam propagation and correction presents many challenges when compared to vertical due to the far harsher turbulent conditions and increased complexity it induces. We investigate the collection of beam propagation data, analysis, and use for building a mathematical model of the horizontal turbulent path and the plans and designs for an adaptive optical system to use this information to correct for horizontal path atmospheric turbulence.

We describe updates in both hardware and software at the Navy Precision Optical Interferometer (NPOI) and our continuous work to expand and extend the capabilities of this instrument for potential Space Situational Awareness (SSA) technological demonstration. The main new topics with respect to our previous work are a campaign of observations carried out in March and then repeated in June and the results of these campaigns. The second area is the procurement of three one-meter diameter telescopes in order to increase the sensitivity of the instrument. Description of the ongoing work for the deployment of these telescopes will be described.

Light field microscope (LFM) is an optical microscope capable of obtaining images having large depth of field with different viewpoints. By using the parallax of these multi-view images, it is possible to reconstruct the 3D sample. However, the sampling interval of this multi-viewpoint image depends on the pitch interval of the microlens array, so the spatial resolution is low, and the accuracy of the 3D sample to be reconstructed is also low. Conventional research has a method of increasing the spatial resolution by subpixel-shifted multiple images. However, this method has problems such as the necessity of mechanical operation and high cost. Therefore, we propose applying Fourier ptychography to the LFM. Fourier ptychography is a technique to obtain high spatial resolution images by joining images obtained by irradiating samples from different angles using LED arrays in Fourier space. Fourier ptychography does not require mechanical scanning and is high throughput and low cost. In addition, Fourier tycoography is possible to obtain phase information on a sample, and it is also possible to obtain a fine 3D sample. We propose a method to generate high spatial resolution multiview images using Fourier ptychography and reconstruct highly accurate 3D sample from those images. In this research, we experiment with the original LFM and verify the effect.

Our system compression method dispenses with signal sparsity and convex optimization on which compressed sensing relies. Hence it may recover signals and images from 25% or less samples in real time and in numerically or perceptually lossless quality. Experimental results manifest that system compression method overwhelmingly outperforms compressed sensing methods in both image quality and computation speed. Demo software and testing results are all downloadable at the website http://qualvisual.net.

This paper describes an approach to coherent aperture synthesis and fine-resolution image reconstruction employing phase retrieval from intensity measurements. A Gerchberg-Saxton algorithm is used on a pair of intensity measurements to obtain the fields for each telescope at each position of the telescopes without a reference beam. These are combined into a larger synthetic aperture, and a cross-correlation is used to sense and correct for piston, tip and tilt phases of each of the sub-apertures with respect one another. Results of simulations, including the effects of speckle, are shown, and practical considerations are evaluated.

We have recently introduced a Miniature Compressive Ultra-spectral Imaging (MUSI) system that is able to capture spectral images from an order of magnitude fewer samples than taken by conventional sensors. The imager is based on a compressive spectral Liquid Crystal modulation which has a thickness of tens of micrometers, making it prone to imperfections and spatial non-uniformity. We present a mathematical algorithm that allows the inference of the spectral transmission over the entire cell area from only a few calibration measurements.

All image correlation based tracking algorithms exhibit some sort of deleterious drift problems. This presentation examines this issue and steps to mitigate it.

This study compares efficiency measurements to efficiency predictions for a digital-holography imaging system operating in the off-axis image plane recording geometry. In practice, we use a highly-coherent 532 nm laser source and an extended Spectralon® object. To compare our efficiency measurements to our efficiency predictions, we make use of an expression for the signal-to-noise ratio (SNR), which contains many multiplicative terms with respect to total-system efficiency. The results show that the polarization and the fringe-integration efficiency terms play the largest role in the total-system efficiency for the digital-holography imaging system.

Digital holography holds several advantages over conventional imaging and wavefront sensing, chief among these being significantly fewer and simpler optical components and the retrieval of complex field. Consequently, many imaging and sensing applications including microscopy and optical tweezing have turned to using digital holography. A significant obstacle for digital holography in real-time applications, such as wavefront sensing for high energy laser systems and high speed imaging for target tracking, is the fact that digital holography is computationally intensive; it requires iterative virtual wavefront propagation and hill-climbing to optimize some sharpness criteria. It has been shown recently that minimum-variance wavefront prediction can be integrated with digital holography and image sharpening to reduce significantly large number of costly sharpening iterations required to achieve near-optimal wavefront correction. This paper demonstrates further gains in computational efficiency with localized sharpening in conjunction with predictive dynamic digital holography for real-time applications. The method optimizes sharpness of local regions in a detector plane by parallel independent wavefront correction on reduced-dimension subspaces of the complex field in a spectral plane.

In MRI the presence of metal implants causes severe artifacts in images. The Dixon method can be used to estimate the magnetic field disturbance and improve the images. However, this requires an undersampled phase estimate to be unwrapped. We have developed POP, an algorithm which unwraps the phase along 1-D paths for a 2-D image, starting well away from the metal implant. Phase is expanded using a smooth periodic basis along each path. In principle, POP can be extended to 3-D imaging (expanding phase over a series of enclosing closed surfaces). Results are presented for 2-D images of phantoms and actual patients.

Understanding the 3D structure of the environment is advantageous for many tasks in the field of robotics and autonomous vehicles. From the robot’s point of view, 3D perception is often formulated as a depth image reconstruction problem. In the literature, dense depth images are often recovered deterministically from stereo image disparities. Other systems use an expensive LiDAR sensor to produce accurate, but semi-sparse depth images. With the advent of deep learning there have also been attempts to estimate depth by only using monocular images. In this paper we combine the best of the two worlds, focusing on a combination of monocular images and low cost LiDAR point clouds. We explore the idea that very sparse depth information accurately captures the global scene structure while variations in image patches can be used to reconstruct local depth to a high resolution. The main contribution of this paper is a supervised learning depth reconstruction system based on a deep convolutional neural network. The network is trained on RGB image patches reinforced with sparse depth information and the output is a depth estimate for each pixel. Using image and point cloud data from the KITTI vision dataset we are able to learn a correspondence between local RGB information and local depth, while at the same time preserving the global scene structure. Our results are evaluated on sequences from the KITTI dataset and our own recordings using a low cost camera and LiDAR setup.

This work proposes an edge sensitive 3D measurement system in which four cameras arraying around a MEMS scanner projecting two directional laser stripe. Firstly, we should calibrate the system parameters of cameras and determine the matrix transformation relationship between calibration plate coordinate system and the camera coordinate system. Secondly, we determine the mask of the region of interest using Fourier transformed and then extract laser stripe center respectively (X axis and Y axis direction) after inverse Fourier transform. Lastly, with binocular stereo reconstruction technique, two sets of point cloud models are converted to the calibration plate coordinate system, we can get 3D model with fine edge step. Compared with traditional method, this method for scanning the mutually perpendicular edges(x direction and y direction) of an object has the advantages of high efficiency, high speed, edges with high precision and structure without rotation device.

Three dimensional interferometric synthetic aperture ladar(SAL) based on the pseudo-random code can get the three dimensional information of the target to reconstruct the original target, overcome the height information loss and satisfy the requirements of high speed imaging. M sequence was used as it is adopted for its superior performance in code compression. The principle of the three dimensional interferometric SAL based on pseudorandom code was theoretical deduced in detail, and the simulation results were given.

Down-looking synthetic aperture imaging ladar have bidirectional (positive and negative direction) modulation in the orthogonal direction of travel during phase modulation. The return signal can be also collected in the two direction. The imaging processing with bidirectional modulation is used and demonstrated. The signal-to-noise ratio can be enhanced in this mode synthetic aperture imaging ladar. Meanwhile, the velocity of carrying-platform can be faster. In the experiment, the return signals with bidirectional modulation are stacked and rebuilt. Compared to the unidirectional modulation imaging, the faster and clearer imaging is realized with bidirectional modulation. This technique has a great potential for applications in extensive synthetic aperture imaging ladar fields.

In Synthetic aperture imaging ladar (SAIL), the polarization state change of the backscattered light will affect the imaging. Polarization state of the reflected field is always determined by the interaction of the light and the materials on the target plane. The Mueller matrices can describe the complex polarization features of the target reflection and treat this interaction. In this paper, the influence on resolution element imaging in side-looking and down-looking SAILs will be theoretically analyzed.

This paper proposes a method, based on the invariant eigenvalue principle of rotation matrix in the turntable coordinate system and the coordinate transformation matrix of the corresponding coordinate points to accomplish a higher accuracy point cloud registration. First of all, we control the rotation angle of the calibration plate with the turntable to calibrate the coordinate transformation matrix of the corresponding coordinate points by using the least squares method. And then we use the feature decomposition to calculate the coordinate transformation matrix of the camera coordinate system and the turntable coordinate system. Compared with the traditional previous method, it has a higher accuracy, better robustness and it is not affected by the camera field of view. In this method, the coincidence error of the corresponding points on the calibration plate after registration is less than 0.1mm.

The fusion of Multi-resolution texture aims to correct the observable discontinuities within global areas and the overlapping areas, which are given from different resolutions, lighting change, non-lambertian object surface, etc. In the paper, we present the acquirer of 3D models with high-resolution textures based on digital image processing and a multi-resolution texture fusion algorithm. the principles of image registration and 3D models registration are introduced in detail, the methods of the light source correction and the global correction are proposed. Finally, the experiments verify the proposed methods, and a lot of tests are done to verify the robustness and effectiveness of the algorithm.

This paper presents a low cost and fast optical 360-degree shape measurement method, which possesses the advantages of full static, fast and low cost. The laser MEMS scanner ensures that laser stripes are always focused on the surface of the object, so that cameras can capture clear modulated laser stripes in mirrors. Meanwhile, a novel stereo calibration technology is presented in this paper that a stereoscopic calibration block with special coded patterns on six sides is used to calculate the transformation matrix for clouds data registration, so that we can get 360-degree models of objects quickly. Compared with the traditional optical 360-degree shape measurement methods, this method does not require extra rotating equipment or more scanners, reducing the cost and saving time.

Possibilities of the image quality enhancement by using multi-aperture systems are investigated numerically for incoherent imaging through atmospheric turbulence. We compare the quality of images formed by a single aperture and images synthesized by an array of N*N subapertures (N = 2–15). The results of correction of images synthesized are compared. It is shown that if the size of a multi-aperture system is constant, then there is an optimal number of subapertures, which depends on the turbulence intensity and diffraction effect. Optimal conditions for the use of multi-aperture imaging versus the atmosphere conditions and distance are found.

Super-resolution is being considered as one of the important goals for optical imaging and image processing. In this paper, we present a novel imaging technique that exceeds the limit of resolving power of diffraction-limited optical system to achieve super-resolution imaging, by combining the advantages of compressive sensing and complex annular filters. This technique is realized by utilizing a classical 4F optical system with a phase-only spatial light modulator. Furthermore, the feasibility of this technique is theoretically analyzed, and physically validated by laboratory experiments. Experimental results have demonstrated that the technique improves the resolving power of diffraction-limited optical system by approximately times, and the intensity image of high-resolution object can be recovered from of the total number of measurements.

We have investigated the spatial-frequency filtering on PDLC. Partial beams passed through LC droplets and polymer matrix may be considered as plane waves passing different optical pathes and interfering in the far zone. Changing the voltage results in changeing the LC effective refractive index leading to a change of the path difference between the interfering beams. The effect of interference decreases of some spectral components of the radiation passing through PDLC sample can be used for space-frequency filtering of images.

A photon counting 3D imaging system with short-pulsed structured illumination and a single-pixel photon counting detector are built. The proposed multiresolution photon counting 3D imaging technique acquires a high-resolution 3D image from a coarse image and details at successfully finer resolution sampled by hadamard multiplexing along the wavelet trees. The detected power is significant increased thanks to the hadamard multiplexing method. Both the required measurements and the reconstruction time can be significant reduced, which makes the proposed technique suitable for scenes with high spatial resolution.

Virtual reality applications provide opportunity to test human vision in well-controlled scenarios that would be difficult to generate in real physical spaces. This study is intended to evaluate the importance of regularity priors used by the human visual system. Using a CAVE simulation, subjects viewed virtual objects in a variety of experimental manipulations, including presence or absence of binocular disparity and color, scene inversion, spatial arrangement of objects in a scene, and aspect ratio of objects. Based on these results, we conclude that gravity, horizontal ground, and symmetry priors play an important role in veridical perception of scenes.

In this paper, we propose ghost imaging using shifted speckles and bucket detection to improve the performance of computational ghost imaging (CGI) in edge detection. The edges of an unknown object is achieved directly without the clear “ghost” images. Numerical simulations and experiments are performed. It is demonstrated that the technique is applicable in noisy environments by using Sobel operator. This provides a great opportunity to pave the way for the real applications of CGI in remote sensing and biological imaging.

There is a vast variety of algorithms of shape from shading. Most of these algorithms rely on basic assumptions about the surface reflective properties, camera projection and location, and the light source distribution. In this paper, we implemented an algorithm based on a linear filtering approach to obtain surface estimation from a single image. The algorithm was tested with images generated synthetically and also with images from a real object. We were able to obtain the shape of objects with few iterations.

An additional step to traditional iterative phase retrieval algorithms is described that allows the reconstruction of an image from the product of its sufficiently sampled far-field diffraction intensity and a second signal. The iterative phasing algorithm with this added step attempts to recover both the image and the multiplicative signal at the same time. Simulations show that reasonable reconstructions of both the original image and the multiplicative signal can be attained in many cases.

Phase retrieval is concerned with reconstructing an image of an object from measurements of only the intensity, but not the phase, of a diffracted field, and occurs in many imaging problems from microscopy to astronomy. Whether a unique, and therefore useful, image can be obtained depends on the particular problem at hand. With new x-ray sources such as x-ray free-electron lasers, there is now the possibility of using 1D or 2D crystalline specimens to image biological molecules. We characterise the properties of the phase problem for the case of 1D and 2D crystals, and analyse the performance of image reconstruction algorithms.

Shadow imaging is a technique to obtain highly resolved silhouettes of resident space objects (RSOs) which would otherwise be unattainable using conventional terrestrial based imaging approaches. Here, we present ongoing research efforts pertaining to shadow imaging of geosynchronous (GEO) satellites. Resolution limits are shown to be independent of wavelength for monochromatic collections, and are then quantified based on the spectral width for polychromatic observations. Image reconstruction is performed using a Fresnel integral based phase retrieval algorithm utilizing Babinet's principle. We also present refinements to our shadow prediction model, as well as our current efforts to physically collect a GEO shadow.

We describe the concept of controlled or natural motion of an object in a spatially varying field magnitude as the basis for coherent optical sensing and imaging. Examples presented are for microscopy with interfering laser beams and speckle formed by scatter from a random medium.

tOSC has developed predictive active imaging system performance for an array of illuminator and receiver subapertures. The receiver need not coincide with the transmitter. The theory provides the array irradiance everywhere on target in the presence of piston errors, and the resulting speckle pattern-induced imaging noise. The principal results are the Signal to Noise Ratios (SNR) for the radiometric and speckle imaging portions of the problem. In this paper, we predict the imaging performance for sample arrays, and verify that performance in simulation and a laboratory brassboard. Our results indicate we can generate active images even for very long-range engagements.

Underwater turbulence occurs due to random fluctuations of temperature and salinity in water and responsible for alteration in water density, refractive index variation and attenuation in light direction. These imposes random geometric distortions, spatio-temporal varying blur, limited range visibility and limited contrast on the acquired images. Conventional restoration algorithms requires computationally intensive image registration, higher CPU load and memory allocations. Thus, we propose a simple patch based dictionary learning algorithm to restore the image by alleviating the computational intensive image registration step which requires lower computational load compared to conventional restoration algorithms and shows better results.

Imaging through underwater experiences severe distortions due to random fluctuations of temperature and salinity in water, which produces underwater turbulence through diffraction-limited blur and lights reflecting from objects of an image perturbs and attenuates contrast, making the recognition of objects of interest difficult. Thus, in underwater imaging the information available for detecting objects of interest is a challenging task because they have inherent confusion among the background, foreground and other image properties. In this study, we propose a fused saliency approach to detect the objects acquired from the image traversed through underwater turbid medium.

We present a user-friendly computational platform for numerical analysis and performance assessment of a wide range of optical systems for imaging and laser projection applications. The wave-optics-based software package, referred to as the Wave-Optics Joint Estimation Toolbox (WaveJET), exploits advantages of GPU/CUDA technologies and allows one to quickly and accurately simulate atmospheric turbulence effects on various systems using the combination of different computational techniques and algorithms for wavefront sensing and imaging. The WaveJET software also takes into account critical system engineering design constraints including system architecture, diffraction, turbulence propagation, adaptive optics control, and coherent/incoherent beam combining.

To get accurate 3D reconstruction of small objects using structured light, it is necessary to modify the optics of commercial projection systems. However, this addition of lenses increases the aberrations, distortions, and nonlinearities in the projection. This generates errors in the phase unwrapping. In this paper we propose an ANN-based model to compensate for phase errors due to nonlinearities such as gamma effect, defocusing and illumination changes. The proposed method is compared with the passive and active methods most used in the literature. The experimental results show that our proposal reduces the effects of nonlinearities, achieving accurate 3D reconstructions.

The atmospheric turbulence is the biggest obstacle to terrestrial astronomical observations. The objective of this study is to estimate these parameters the case of observation of the sun by the statistical analysis of arrival angle fluctuation and this can be directly obtained from the observations of the solar edge.

Typically, the cost of a space-borne imaging system is driven by the size and mass of the primary aperture. The solution that we propose uses a method to construct an imaging system in space in which the nonlinear optical properties of a cloud of micron-sized particles, shaped into a specific surface by electromagnetic means, and allows one to form a very large and lightweight aperture of an optical system, hence reducing overall mass and cost. Recent work at JPL has investigated the feasibility of a granular imaging system, concluding that such a system could be built and controlled in orbit.

Speckle elimination via coherence reduction is currently being investigated as a means of improving the quality of images obtained with laser illumination. Homogenizing light pipes provide one avenue of altering the spatial coherence properties of a laser source for this purpose. This paper models the propagation of a partially coherent source in a light pipe via propagation of the cross-spectral density. Though direct numerical propagation of the cross-spectral density is computationally burdensome, immense simplifications are possible for the class of partially coherent sources known as Schell-model sources. The cross-spectral density of a Schell-model source may be represented as the convolution of a coherent “mode” with a weighting function. Mathematically, propagation of this mode can precede evaluation of the convolution. Discretization and numerical evaluation of the convolution casts this approach as a “finite-element source” approach, wherein individual identical modes are propagated and superposed to obtain the propagated cross-spectral density. The end result is that the 4-dimensional integral needed to propagate the cross-spectral density is replaced by the 2-dimensional integral needed to propagate the individual mode. In this paper, this method of propagation is baselined to analytic results for free space propagation, and then used to model the evolution of coherence within a homogenizing light pipe. The conditions necessary to achieve uniform illumination via projection of the waveguide exit field are discerned and discussed, and the speckle mitigation capabilities of the setup are modeled and assessed.

We present the study of a geometrical optics computer simulation approach for a series of short-exposure, incoherent image realizations. This type of simulation allows the study of the dynamic nature of turbulence and its effect on imaging. We discuss replacing the commonly used wave optics propagation simulation approach with a geometrical optics approach where rays are traced through split-step turbulence screens to create incoherent imagery. We review the limitations of geometric optics for turbulence scenarios and identify the parameter regimes where ray tracing may be valid for incoherent image simulation. We present a ray tracing approach and demonstrate the computation time speedup compared to wave optics.

The possibilities of passive crosswind profiling based on the analysis of image distortion evolution caused by the wind drift of turbulent air inhomogeneities are studied. A possibility of determining the wind speed for several (at least three) turbulent layers is shown numerically. Based on the comparison with contact measurements (using 10 acoustic anemometers along the path 500 m long) of a wind speed, the method showed satisfactory accuracy in determining the wind speed for atmospheric layers close to the observer, as well as the average wind speed along the entire observation path.