Framework for improving DoLP and AoLP reconstruction quality in microgrid polarimeters.

In polarimetric imaging, degree and angle of linear polarization (DoLP and AoLP, respectively) are computed from ratios of Stokes parameters. In snapshot imagers, DoLP and AoLP are degraded by inherent mismatches between the spatial bandwidth of the S0, S1, and S2 parameters reconstructed by demosaicking from microgrid polarizer array (MPA)-sampled data. To overcome this, we rigorously show that log-MPA-sampled data approximately decouples DoLP and AoLP from the intensity component (S0) in the spatial Fourier domain. Based on this analysis, we propose an alternative demosaicking strategy aimed at estimating DoLP and AoLP directly from MPA-sampled data. Our method bypasses Stokes parameter estimation, alleviating the spatial bandwidth mismatch problems altogether and reducing computational complexity. We experimentally verify the superior DoLP and AoLP reconstructions of the proposed log-MPA demosaicking compared to the conventional Stokes parameter demosaicking approach in simulation. We simulated the conventional 2 × 2 MPA patterns as well as the more recently introduced 2 × 4 MPA patterns, and report quantitative results (mean squared error, structural similarity index, and polarization angular error) using five demosaicking approaches drawn from the literature. We also provide a closed-form error analysis on the log-MPA-sampled data to demonstrate that the approximation error is negligible for real practical applications.

Joint object classification and turbulence strength estimation using convolutional neural networks.

In a recent paper, Kee et al. [Appl. Opt.59, 9434 (2020)APOPAI0003-693510.1364/AO.405663] use a multilayer perceptron neural network to classify objects in imagery after degradation through atmospheric turbulence. They also estimate turbulence strength when prior knowledge of the object is available. In this work, we significantly increase the realism of the turbulence simulation used to train and evaluate the Kee et al. neural network. Second, we develop a new convolutional neural network for joint character classification and turbulence strength estimation, thereby eliminating the prior knowledge constraint. This joint classifier-estimator expands applicability to a broad range of remote sensing problems, where the observer cannot access the object of interest directly.

United States Air Force Research Laboratory: introduction to the focus issue.

This focus issue on the United States Air Force Research Laboratory (AFRL) spans the latest trends in imaging and detectors, atmospheric characterization, laser sources and propagation, optics and optical assemblies, optical characterization of materials, photonics, optical processing, and machine learning for applications that cover everything from stellar interferometry to studying damage to the plasma membranes of living cells.

Airborne validation of the general image quality equation 5.

The general image quality equation (GIQE) maps imaging system parameters to performance in terms of common detection and recognition tasks. Changes to the National Imagery Interpretation Rating Scale led to the development of GIQE version 5 in 2015. The purpose of this paper is to provide a review of GIQE 5 applications in the literature, a tutorial on its use, and, for the first time , an independent validation of the new model along with comparisons to GIQEs 3 and 4.

Spatial stabilization of deep-turbulence-induced anisoplanatic blur.

We explore the feasibility of post-detection restoration when imaging through deep turbulence characterized by extreme anisoplanatism. A wave-optics code was used to simulate relevant short-exposure point spread functions (PSFs) and their decorrelation as a function of point-source separation was computed. In addition, short-exposure images of minimally extended objects were simulated and shown to retain a central lobe that is clearly narrower than the long-exposure counterpart. This suggests that short-exposure image data are more informative than long-exposure data, even in the presence of extreme anisoplanatism. The implications of these findings for image restoration from a sequence of short-exposure images are discussed.

Improved microgrid arrangement for integrated imaging polarimeters.

For almost 20 years, microgrid polarimetric imaging systems have been built using a 2×2 repeating pattern of polarization analyzers. In this Letter, we show that superior spatial resolution is achieved over this 2×2 case when the analyzers are arranged in a 2×4 repeating pattern. This unconventional result, in which a more distributed sampling pattern results in finer spatial resolution, is also achieved without affecting the conditioning of the polarimetric data-reduction matrix. Proof is provided theoretically and through Stokes image reconstruction of synthesized data.

Stokes image reconstruction for two-color microgrid polarization imaging systems.

The Air Force Research Laboratory has developed a new microgrid polarization imaging system capable of simultaneously reconstructing linear Stokes parameter images in two colors on a single focal plane array. In this paper, an effective method for extracting Stokes images is presented for this type of camera system. It is also shown that correlations between the color bands can be exploited to significantly increase overall spatial resolution. Test data is used to show the advantages of this approach over bilinear interpolation. The bounds (in terms of available reconstruction bandwidth) on image resolution are also provided.

Super-resolution for imagery from integrated microgrid polarimeters.

Imagery from microgrid polarimeters is obtained by using a mosaic of pixel-wise micropolarizers on a focal plane array (FPA). Each distinct polarization image is obtained by subsampling the full FPA image. Thus, the effective pixel pitch for each polarization channel is increased and the sampling frequency is decreased. As a result, aliasing artifacts from such undersampling can corrupt the true polarization content of the scene. Here we present the first multi-channel multi-frame super-resolution (SR) algorithms designed specifically for the problem of image restoration in microgrid polarization imagers. These SR algorithms can be used to address aliasing and other degradations, without sacrificing field of view or compromising optical resolution with an anti-aliasing filter. The new SR methods are designed to exploit correlation between the polarimetric channels. One of the new SR algorithms uses a form of regularized least squares and has an iterative solution. The other is based on the faster adaptive Wiener filter SR method. We demonstrate that the new multi-channel SR algorithms are capable of providing significant enhancement of polarimetric imagery and that they outperform their independent channel counterparts.

Multichannel blind deconvolution of polarimetric imagery.

A maximum likelihood blind deconvolution algorithm is derived for incoherent polarimetric imagery using expectation maximization. In this approach, the unpolarized and fully polarized components of the scene are estimated along with the corresponding angles of polarization and channel point spread functions. The scene state of linear polarization is determined unambiguously using this parameterization. Results are demonstrated using laboratory data.

Fundamental estimation bounds for polarimetric imagery.

Precise channel-to-channel registration is a prerequisite for effective exploitation of passive polarimetric imagery. In this paper, the Cramer-Rao bound is employed to determine the limits of registration precision in the presence of scene polarization diversity, channel noise, and random translational registration errors between channels. The effects of misregistration on Stokes image estimation are also explored in depth. The derived bound is then used to determine when joint estimation is preferable to externally provided registration correction. Finally, case studies are presented for polarization insensitive imagery (a special case) and linear polarization imaging systems with three and four channels. An optimum polarization channel arrangement is also proposed in the context of the bound.