This PDF file contains the front matter associated with SPIE Proceedings Volume 8877, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

The individual phases of a multi-beamlet laser source can be manipulated by exploiting high-bandwidth phase loops to correct for aberrations induced within the optical beamlet trains. With the current state of the art in phasing technology, this phasing of the beamlet trains is successfully accomplished up to a common aperture sharing element or on a pointsource target; however, in the presence of an extended target, rough surface scattering through laser-target interaction adds the additional constraints of speckle and depolarizing effects. In particular, speckle phenomena and atmospheric effects create unobservable modes in the beam control system. One such unobservable mode is termed stair mode and is appropriately identified by a stair-step pattern of piston phase across the individual subapertures that comprise a tiled aperture. This paper investigates the effects of turbulence and thermal blooming on phased beam projection from tiled apertures using wave-optics simulations. To represent different array fill factors in the source plane, both seven and 19 element hexagonal close-packed tiled apertures are used in the simulations along with both Gaussian and flat-top outgoing beamlets. Peak Strehl ratio and power in the bucket are calculated in the target plane over multiple random realizations that are then averaged. This is done for all simulation setups with and without the presence of stair mode.

We are developing an adaptive optics system for earth observing remote sensing sensor. In this system, high spatial resolution has to be achieved by a lightweight sensor system to be used for small satellites. Moreover, simple hardware architecture has to be selected to achieve high reliability and low development cost. Image based AOS realize these requirements without wavefront sensor. In remote sensing, it is difficult to use a reference point source unless the satellite controls its attitude toward a star. We propose the control algorithm of the deformable mirror on the basis of two methods; model-based wavefront estimation method and direct optimization of acquired images. We described simulation results of the proposed methods.

Aero-optic aberrations that effect optical sensor performance and laser beam propagation, can be caused by changes in the index-of-refraction field as the optical wave traverses a compressible non-uniform, turbulent flowfield. Mean flowfield non-uniformities cause bore sight error and blurring and, if the mean flowfield is unsteady, jitter. Turbulence causes blurring and high frequency jitter. Blurring also causes the signal-to-noise ratio to decrease and image distortion, and adversely affects centroid location for precision tracking. The objective of this study is to develop an unified approach for whole-field aero-optics prediction using hybrid LES/RANS (Large Eddy Simulation/Reynolds Average Navier-Stokes) turbulence modeling in combination with a newly formulated optical Modulation Transfer Function (MTF). The whole field turbulence includes the near-vehicle boundary layer mean and turbulence, as well as far-field atmospheric turbulence. A flat plate compressible boundary layer case is used to demonstrate the methodology. the abstract two lines below author names and addresses.

The classical methods of compressed coded aperture (CCA) still require an optical sensor with high resolution, although the sampling rate has broken the Nyquist sampling rate already. A novel architecture of multi-shot compressed coded aperture imaging (MCCAI) using a low resolution optical sensor is proposed, which is mainly based on the 4-f imaging system, combining with two spatial light modulators (SLM) to achieve the compressive imaging goal. The first SLM employed for random convolution is placed at the frequency spectrum plane of the 4-f imaging system, while the second SLM worked as a selecting filter is positioned in front of the optical sensor. By altering the random coded pattern of the second SLM and sampling, a couple of observations can be obtained by a low resolution optical sensor easily, and these observations will be combined mathematically and used to reconstruct the high resolution image. That is to say, MCCAI aims at realizing the super resolution imaging with multiple random samplings by using a low resolution optical sensor. To improve the computational imaging performance, total variation (TV) regularization is introduced into the super resolution reconstruction model to get rid of the artifacts, and alternating direction method of multipliers (ADM) is utilized to solve the optimal result efficiently. The results show that the MCCAI architecture is suitable for super resolution computational imaging using a much lower resolution optical sensor than traditional CCA imaging methods by capturing multiple frame images.

It is well known that atmospheric turbulence corrupts the phase front of laser beam propagation. The phase distortions manifest themselves as intensity fluctuations when the beam is propagated over some distance. This intensity fluctuation is often referred to as scintillation. Laser illuminated imaging systems are used for a variety of applications including night time imaging and tracking. The illuminator intensity fluctuation is often considered a noise effect on the imagery, however if an estimate of the scintillation can be separated from the images, it would be useful in estimating atmospheric turbulence parameters. In past work we have used a Bayesian estimation approach to separate the illuminator fluctuations from the target images. In this paper we extend that approach to included calculations of the spatial and temporal statistics of the scintillation estimate to extract atmospheric turbulence parameters

A wave-optics model is developed which allows simulation of an Inverse Synthetic Aperture LADAR (ISAL) imaging system. This end-to-end tool models the complex interactions of Linear Frequency Modulated (LFM) chirped pulses, object/beam interactions including object articulation, speckle phenomenology, heterodyne detection with noise, atmospheric turbulence, and laser-guide star adaptive optics. Detected signal outputs are simulated and processed to explore system design trades and to test and compare image processing algorithms. Model verification results will be presented as well as reconstructed images.

Multiple scattering of light in highly disordered medium can break the diffraction limit of conventional optical system combined with image reconstruction method. Once the transmission matrix of the imaging system is obtained, the target image can be reconstructed from its speckle pattern by image reconstruction algorithm. Nevertheless, the restored image attained by common image reconstruction algorithms such as Tikhonov regularization has a relatively low signal-tonoise ratio (SNR) due to the experimental noise and reconstruction noise, greatly reducing the quality of the result image. In this paper, the speckle pattern of the test image is simulated by the combination of light propagation theories and statistical optics theories. Subsequently, an adaptive total variation (ATV) algorithm—the TV minimization by augmented Lagrangian and alternating direction algorithms (TVAL3), which is based on augmented Lagrangian and alternating direction algorithm, is utilized to reconstruct the target image. Numerical simulation experimental results show that, the TVAL3 algorithm can effectively suppress the noise of the restored image and preserve more image details, thus greatly boosts the SNR of the restored image. It also indicates that, compared with the image directly formed by ‘clean’ system, the reconstructed results can overcoming the diffraction limit of the ‘clean’ system, therefore being conductive to the observation of cells and protein molecules in biological tissues and other structures in micro/nano scale.

In this paper we introduce two novel methods for application of `1-minimization. In the first method, sparse and low-rank decomposition and compressive sensing-based retrieval are combined and applied to a low power surveillance model. The method exploits the ability of sparse and low-rank decompositions to extract significant and stationary features and the ability of compressive sensing approaches to reduce the number of measurements necessary. In the second method, a contiguity prior is added to compressive sensing methods on images and a numerical approach is proposed to solve this novel problem. Results are displayed in which the contiguity constrained method is applied to the low power surveillance model.

We describe a foveated compressive sensing approach for image analysis applications that utilizes knowledge of the task to be performed to reduce the number of required measurements compared to conventional Nyquist sampling and compressive sensing based approaches. Our Compressive Optical Foveated Architecture (COFA) adapts the dictionary and compressive measurements to structure and sparsity in the signal, task, and scene by reducing measurement and dictionary mutual coherence and increasing sparsity using principles of actionable information and foveated compressive sensing. Actionable information is used to extract task-relevant regions of interest (ROIs) from a low-resolution scene analysis by eliminating the effects of nuisances for occlusion and anomalous motion detection. From the extracted ROIs, preferential measurements are taken using foveation as part of the compressive sensing adaptation process. The task-specific measurement matrix is optimized by using a novel saliency-weighted coherence minimization with respect to the learned signal dictionary. This incorporates the relative usage of the atoms in the dictionary. Therefore, the measurement matrix is not random, as in conventional compressive sensing, but is based on the dictionary structure and atom distributions. We utilize a patch-based method to learn the signal priors. A treestructured dictionary of image patches using KSVD is learned which can sparsely represent any given image patch with the tree-structure. We have implemented COFA in an end-to-end simulation of a vehicle fingerprinting task for aerial surveillance using foveated compressive measurements adapted to hierarchical ROIs consisting of background, roads, and vehicles. Our results show 113x reduction in measurements over conventional sensing and 28x reduction over compressive sensing using random measurements.

Many imaging techniques provide measurements proportional to Fourier magnitudes of an object, from which one attempts to form an image. One such technique is intensity interferometry which measures the squared Fourier modulus. Intensity interferometry is a synthetic aperture approach known to obtain high spatial resolution information, and is effectively insensitive to degradations from atmospheric turbulence. These benefits are offset by an intrinsically low signal-to-noise (SNR) ratio. Forward models have been theoretically shown to have best performance for many imaging approaches. On the other hand, phase retrieval is designed to reconstruct an image from Fourier-plane magnitudes and object-plane constraints. So it’s natural to ask, “How well does phase retrieval perform compared to forward models in cases of interest?” Image reconstructions are presented for both techniques in the presence of significant noise. Preliminary conclusions are presented for attainable resolution vs. DC SNR.

An approach is presented for numerically simulating incoherent imaging using coherent wave optics propagation methods. The approach employs averaging of irradiance from uncorrelated coherent waves to produce incoherent results. Novel aspects of the method include 1) the exploitation of a spatial windowing feature in the wave optics numerical propagator to limit the angular spread of the light and 2) a simple propagation scaling concept to avoid aliased field components after the focusing element. Classical linear systems theory is commonly used to simulate incoherent imaging when it is possible to incorporate aberrations and/or propagation medium characteristics into an optical transfer function (OTF). However, the technique presented here is useful for investigating situations such as “instantaneous” short-exposure imaging through distributed turbulence and phenomena like anisoplanatism that are not easily modeled with the typical linear systems theory. The relationships between simulation variables such as spatial sampling, source and aperture support, and intermediate focal plane are discussed and the requirement or benefits of choosing these in certain ways are demonstrated.

Many imaging modalities measure magnitudes of Fourier components of an object. Given such data, reconstruction of an image from data that is also noisy and sparse is especially challenging, as may occur in some forms of intensity interferometry, Fourier telescopy, and speckle imaging. In such measurements, the Fourier magnitudes must be positive, and moreover must be less than 1 given the usual normalization, scaling the magnitudes so that the magnitude is one at zero spatial frequency in the u-v plane data. The Cramér-Rao formalism is applied to single Fourier magnitude measurements to ascertain whether a reduction in variance is possible given these constraints. An extension of the Cramér-Rao formalism is used to address the value of relatively general prior information. The impact of this knowledge is also shown for simulated image formation for a simple disk, with varying measurement SNR and sampling in the (u,v) plane.

Fourier telescopy is an active unconventional imaging technique. Three or more beams from different spatially separated transmitters are pointed at a distant and faint object. The spatial Fourier spectrum of the object is carried on the reflected temporally modulated signals. The image of the target can be reconstructed from the back signals by demodulation and phase closure algorithm. The conventional demodulation processing is calculating spectrum directly by inverse Fourier transform of the signal. However spectrum estimated by inverse Fourier transform has non-negligible errors caused by frequency shift error of the Acoustic-optical modulator, the noise and the relative motion between beams and the target. An improved demodulation method based on spectrum correction of FT is proposed. The method corrects the amplitude and the phase on the demodulated frequency of the signal by which better reconstructed image can be obtained. In this paper, the effect of the frequency shift error in Fourier telescopy demodulation is investigated. The degradation of the reconstructed image is simulated. We summarize the new demodulation method based on spectrum correction and give the simulated comparison between the conventional demodulation and the developed method. The result confirms the effectiveness of the improved demodulation method.

As synthetic aperture imaging ladar employs the linear chirp laser signal, it is inevitably impacted by the space-time varying speckle effect. In many SAIL two-dimensional reconstructed images, the laser speckle effect severely reduces the image quality. In this paper, we analyze and simulate the influence of space-time speckle effect to the resolution element imaging both in range direction and in azimuth direction. Expressions for two-dimensional data collection contained space-time speckle effect are obtained, and computer simulation results of resolution degradation both in range direction and in cross-range direction are presented.

The synthetic aperture imaging ladar (SAIL) systems typically generate large amounts of data difficult to compress with digital method. This paper presents an optical SAIL processor based on compensation of quadratic phase of echo in azimuth direction and two dimensional Fourier transform. The optical processor mainly consists of one phase-only liquid crystal spatial modulator(LCSLM) to load the phase data of target echo and one cylindrical lens to compensate the quadratic phase and one spherical lens to fulfill the task of two dimensional Fourier transform. We show the imaging processing result of practical target echo obtained by a synthetic aperture imaging ladar demonstrator. The optical processor is compact and lightweight and could provide inherent parallel and the speed-of-light computing capability, it has a promising application future especially in onboard and satellite borne SAIL systems.

Synthetic aperture laser imaging ladar’s optical receiver is a heterodyne detect system, so the atmosphere turbulence will affect the phase history of the ladar seriously. Unlike in conventional passive optical imaging system, both the wavefront distortion and piston term will decrease the imaging resolution. The distortion of the wavefrom decreases the heterodyne mixing efficient; the piston will cause the pulse-to-pulse phase errors. Multiaperture receiver technology can improve the heterodyne mixing efficient efficiently, but the pattern of multiaperture should be optimized according to different turbulence intensity. In this paper, we optimize a four-aperture receiver pattern in different turbulence environment. The simulation and experiment results are obtain in our ladar system.