This PDF file contains the front matter associated with SPIE Proceedings Volume 12690, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

The Applied Sensing Laboratory at the University of Dayton has constructed a solar simulation laboratory to support polarimetric remote sensing research. The laboratory contains a number of highly accurate and repeatable motion stages that allow for automated positioning and control of imaging sensors, light sources, and object geometries. The laboratory contains both collimated (direct sun) and diffuse (downwelling) light sources that we have spectrally tuned to match expected solar irradiance under a range of outdoor conditions. In this work we describe the capabilities of the laboratory and the measures that have been taken to date for calibrating the laboratory environment to mimic outdoor solar conditions. The laboratory can support complex, automated experiments that can precisely control the dominant parameters of interest in polarimetric remote sensing. We demonstrate example data for laboratory use cases of interest to the polarimetric imaging community that include polarimetric bidirectional reflectance distribution function (pBRDF) measurements and generation of curated datasets to support polarimetric phenomenology studies and deep learning algorithm training for a host of polarimetric remote sensing applications.

Our group previously presented an empirical approach for measuring the polarimetric bidirectional reflectance distribution function (pBRDF) using a visible linear imaging polarimeter from 3D painted geometric objects with well-characterized surface facets. The initial results obtained from this approach were validated against physics-based models and demonstrated good agreement with data collected under outdoor, full-sun conditions. In this work, we conduct similar measurements on the same faceted objects in a laboratory environment. The Applied Sensing Lab at the University of Dayton has constructed a solar simulation laboratory that allows for highly accurate and repeatable positioning of light sources, sensors, and objects. The laboratory contains both collimated (direct sun) and diffuse (downwelling) light sources that we have spectrally tuned to match expected solar irradiance under a range of outdoor conditions.

Closed-form solutions for shape-from-polarization (SfP) generally assume either purely specular or purely diffuse polarized light scattering models. However, polarized light scattering from real-world objects is a mixture of both of these processes. This work makes use of a closed-form expression for polarized light scattering model which combines specular and diffuse contributions. In prior work, we have demonstrated the broad applicability of a triply-degenerate (TD) model which decouples depolarization from the dominant Mueller-Jones matrix (MJM). The depolarization is controlled by a single parameter and the MJM encodes the polarization-dependent properties (e.g. diattenuation, polarizance). In this work, SfP information content is explored using our model for the MJM term which combines diffuse and specular polarization to simulate single-view, noise-free Mueller images. A merit function for simultaneous estimates of per-pixel surface normal and absolute depth is proposed. Cross-sections of this merit function are shown to be convex along depth and contain erroneous ambiguities for the surface normal. While ambiguities in surface normal estimates are well known for existing SfP approaches, these cross-sections show a kind of ambiguity unique to our model. Through investigation of the idealized scenario of an exactly-known pBRDF model and noise-free, infinitely precise polarimetric measurements, we found that simultaneous depth and shape estimation is achievable.

It is well known that underwater objects become more readily visible when viewed through a vertical polarizer that suppresses horizontally polarized reflections from the air-water interface. However, quantitative measurements of the contrast enhancement achieved with a polarizer do not seem to have been reported in the literature. To measure the polarization-enabled contrast enhancement, we placed white and black tiles next to each other, immersed in water, then measured the optical contrast between them as a function of viewing angle (relative to the surface normal) with a polarization camera that simultaneously recorded images with linear polarization oriented 0°, 90°, and 45°from horizontal. Images were recorded with an RGB polarization camera through approximately 45 cm of water at Bozeman Pond and with a monochrome polarization camera through approximately 5 cm of water at Bozeman Beach. Images also were recorded with the monochrome camera and a filter to isolate the near infrared band of approximately 750 to 1000 nm. Indoor laboratory measurements also were recorded to verify the role of the color of the reflecting background. All experiments used carefully calibrated division-of-focal-plane polarization cameras. The observed contrast decreased with viewing angle, but less so for the vertically polarized images. The contrast enhancement, represented by the ratio of vertically polarized to unpolarized contrast, increased with viewing angle, even past the Brewster angle (approx. 53°). The contrast enhancement only began decreasing for viewing angles larger than 70°. In outdoor experiments with a mostly clear sky, the highest contrast enhancement was in the blue spectral band. The contrast was essentially the same for red, green, and blue bands with a white background. In all measurements, the black tile exhibited much larger degree of linear polarization, which is an example of the Umov effect. In this paper we describe the experiments, show and explain polarization images, and show and explain plots of contrast and contrast enhancement as a function of viewing angle.

The advent of polarization-sensitive cameras opens the avenue for real-time in-vivo polarimetric diagnostic imaging of biological tissues in clinical settings, but this approach allows measuring only the first three rows of 4×4 Mueller matrix. In order to extract diagnostically relevant images of tissue linear retardance, azimuth of the optical axis and depolarization from the partial Mueller matrix we have formulated a theoretical framework for the decomposition of 3×4 Mueller matrices and tested its validity on both simulated data for optical phantoms and experimental data collected from thick sections of formalin-fixed human brain measured in reflection. The polarimetric maps calculated with our algorithm and Lu-Chipman polar decomposition of the complete Mueller matrices demonstrate compelling correlation and preserve diagnostic image contrast.

We present a summarized and simplified introduction to our wave description of geometric phase. We start by discussing the addition of cosine waves of different amplitudes and a phase between them, from which immediately arises the geometric phase in 1D. We then expand on the analysis to the 2D case using the orthogonal components of a polarized light wave. We then show a graphic visualization that facilitates the analysis of geometric phase and use it to quantify the geometric phase obtained by passing different states of polarization through a quarter wave plate.

This presentation will give an overview of the local description of polarization for nonparaxial light, for which all three Cartesian components of the electric field are significant. The polarization of light at each point is characterized by a three-component complex vector in the case of full polarization and by a 3×3 polarization matrix for partial polarization. Standard concepts in paraxial polarization such as the degree of polarization, the Stokes parameters, and the Poincaré sphere, have generalizations for nonparaxial light that are not unique and/or not trivial. Particular emphasis is placed on geometric interpretations and their similarities and differences with those for the paraxial regime, as well as topological features. An application of this formalism in super-resolution microscopy is presented.

An unsettled discussion on the bounds of the geometric phase motivates us to explore its differences with the propagation phase. We prepare an experiment that allows us to modify both phases in the same setup and record the effect this has on white light interference fringes. Our results show clear differences between the phases where the propagation phase moves the white light interference pattern as a whole but the geometric phase does not. We present the addition of the geometric phase as we stack two retarders and compare it to the addition of the propagation phase obtained when stacking two glass windows.

We outfitted a polarimetric microgrid sensor with standard c-mounted lenses and observed inconsistencies in the linear polarimetric response across the focal plane, particularly in the corners. We provide details of our polarimetric image calibration process to mitigate these inconsistencies and display processed results. Standard dark correction and gain calibration improved intensity uniformity, but polarized Mueller calibration was needed to correct variability in polarimetric response at the pixel level. We improved our Mueller calibration process through the addition of an Arduino-controlled rotating analyzer to capture uniform polarimetric scenes. This made the Mueller data collection process significantly easier, more repeatable, and resulted in improved polarimetric Stokes products. Details of the device and examples of how it improved results are shared.

A few polarization image datasets depicting real world scenes have been reported. Some of them are available on an open-data basis. Some databases contain color images, often with color bands reconstructed from a sensor equipped with a Bayer filter. Unfortunately, even if these real-world images depict a variety of objects and situations and have a good overall quality (ie the spectral bands and the various polarization channels are or can be registered, noise is reduced), they often have a low definition (smaller than 1 Mp), a low bit depth and are captured with a large lens aperture, resulting in very band-limited images. Moreover, the demosaicing procedure used to reconstruct the various color bands has a smoothing effect, reducing their resolution. This latter point proves detrimental when it comes to use these images as references for demosaicing algorithms, especially for RGB images: since each channel combining polarization direction and spectral band is very sparse in the base mosaic pattern, artifacts likely to appear are considerably underestimated with band-limited images. In this work, we review existing polarization image databases, focus on non-mosaiced datasets and propose a technique to produce HD polarization images with superior quality.

The stress optic coefficient of an infrared transmitting material was measured at room temperature at a wavelength of 1550nm. This work discusses a Mueller matrix imaging experiment to measure the stress optic coefficient, observe the spatial distribution of birefringence, and quantify experimental sources of uncertainty. A one-inch diameter disk of sample material was diametrically loaded with increasing force, and linear retardance was measured in the central region. Finite element and analytical modeling was done to estimate the magnitude of stress in this central region. A Rotating Retarder Mueller Matrix Imaging Polarimeter measured the spatial distribution of linear retardance. The retardance is related to the change in birefringence with stress magnitude. The slope of this linear fit is the stress optic coefficient. The stress optic coefficient of the infrared transmitting material was measured to be 1.89 ± 0.1424 [TPa]⁻¹. To test the precision of our stress optic coefficient measurement procedure, a 1-inch diameter N-BK7 disk was measured at a wavelength of 1550nm and compared with industry-accepted values. The stress optic coefficient of N-BK7 was measured as 2.83 ± 0.1057[TPa]⁻¹. The published N-BK7 value measured at visible wavelengths is 2.77 [TPa]⁻¹ ± 3%.^1–3 This agreement validates the experimental Mueller matrix imaging methods and supports the common assumption of minor wavelength dependence of the stress optic coefficient.

We discovered a theoretical link between the reflectivity of a solid surface and the resulting polarization, and we are applying this discovery to advance the state-of-the-art of polarimetric remote sensing. At 45◦ incidence angle, a cloud of spectral points in the plot of polarization versus reflectivity collapses into a degenerate, 1-dimensional curve (termed the U-curve) that applies to all materials, both conductors and dielectrics, and starting from first principles, we have derived the analytic equations for the functions P(R) and the inverse, R(P). The curve shows an inverse relationship between polarization and reflectivity and provides a new theoretical underpinning to explain why dark objects are more polarizing than brighter ones. We claim that the U-curve represents the maximum achievable polarization for a surface of given reflectivity at 45◦ incidence. In this work, we measure the spectral polarization and reflectivity of a gold mirror and show that the data are coincident with the U-curve for the spectral region 400-2000 nm, validating the theory. In complementary work, we measure the spectral polarization and reflectivity of less smooth surfaces (copper, silver, crystalline minerals) and demonstrate that increasing surface roughness decreases polarization, moving the data points below the U-curve. We also measure surface roughness of the same materials using an optical profilometer and show that the quantified surface roughness is well correlated with the measured polarization when normalized by the U-curve. This new normalized polarization has been given the name PReMA, which stands for the Polarization Relative to the Maximum Achievable.

Stress-induced birefringence is created by the manufacturing process of injection-molded lenses. Characterizing the degradation in optical performance is important information to guide manufacturing improvements. The 3D birefringence distribution is proportional to the inhomogenous stress field. Birefringence is an anistropic property therefore retardance measurements change if the optical component is rotated. Reconstruction of a 3D birefringence distribution from a series of retardance measurements poses a challenge due to the extension of tomographic algorithms to tensor-valued quantities. Our approach is a closed-form forward model to linearly relate the polarimetric measurements to a line projection through an discrete arrangement of index ellipsoids. The rank of this linear system is investigated for varying arrangements of index ellipsoids. For example, given an homogenous birefringence distribution, only three non-parallel line projections are required for a full-rank operator that reconstructs the index ellipsoid of a planar slice. These three line projections are full-rank for some arrangements of three unique index ellipsoids and rank deficient for others. This mathematical framework is developed to design a tomographic polarimeter for inspecting the stress-induced 3D birefringence distribution of injection-molded optics.

Polarization observations through the next-generation large telescopes will be invaluable for exploring the magnetic fields and composition of jets in AGN, multi-messenger transients follow-up, and understanding interstellar dust and magnetic fields. The 25m Giant Magellan Telescope (GMT) is one of the next-generation large telescopes and is expected to have its first light in 2029. The telescope consists of a primary mirror and an adaptive secondary mirror comprising seven circular segments. The telescope supports instruments at both Nasmyth as well as Gregorian focus. However, none of the first or second-generation instruments on GMT has the polarimetric capability. This paper presents a detailed polarimetric modeling of the GMT for both Gregorian and folded ports for astronomical B-K filter bands and a field of view of 5 arc minutes. At 500nm, The instrumental polarization is 0.1% and 3% for the Gregorian and folded port, respectively. The linear to circular crosstalk is 0.1% and 30% for the Gregorian and folded ports, respectively. The Gregorian focus gives the GMT a significant competitive advantage over TMT and ELT for sensitive polarimetry, as these telescopes support instruments only on the Nasmyth platform. We also discuss a list of polarimetric science cases and assess science case requirements vs. the modeling results. Finally, we discuss the possible routes for polarimetry with GMT and show the preliminary optical design of the GMT polarimeter.

Stokes polarimeters measure some or all the Stokes parameters of a light beam. To reduce the effect of noise in the measurements made on the final calculated Stokes parameters, a polarimeter can be optimized by minimizing the condition number of the characteristic or instrument matrix. However, this optimization does not guarantee the best stability in the presence of experimental errors in the polarimeter configuration. This is particularly important for polarimeters using liquid-crystal variable retarders, which have we have found have errors in the retardance as a function of position in the aperture of the liquid-crystal cell, and fast axis angles as a function of the applied voltage, so even the best aligned of this type of system will have these errors. We have found that different optimized polarimeter configurations can have very different sensitivity to experimental errors. In this work, we present an analysis of a number of different optimized systems to find the most stable configuration with respect to experimental errors. In particular, we consider the variation of the volume of the solid formed in the Poincaré sphere by the Stokes vector values used in each polarimeter configuration.

Multi-domain modulated polarimeters offer benefits such as an increased channel separation in the frequency domain, allowing a reduction in cross-talk and improving their performance in the retrieval of the polarization information. Although the experimental implementation of this kind of system cannot be realized with perfect, periodic modulation due to practical limitations, machine learning methods have been used to obtain the correct calibration parameters and reduce errors during the data reduction stage. The aforementioned strategies have improved the performance of modulated polarimeters. However, in the modulated polarimetric systems reported in the literature, the modulation parameters are set during the design stage and remain unchanged during operation. In this work, we present a dynamic, spatially channeled, imaging Mueller matrix polarimeter in which the modulation parameters of the polarization state generator (PSG) can be adjusted during operation to achieve better performance depending on the spatial frequency properties of the scene under analysis. We present experimental evidence of the feasibility of the method, discuss its capabilities and current limitations, and describe a strategy to retrieve the Mueller matrix of a scene.

The University of Arizona Polarization Lab developed an Infrared Channeled Spectro-Polarimeter (IRCSP) to measure linear Stokes parameters with 1K polarimetric accuracy and 1μm average spectral resolution between 8-11μm. Emissivity and refractive index in this spectral band are known to depend upon water’s kinetic temperature and thermodynamic phase. In this work, the theoretical thermodynamic phase discrimination capabilities of spectral Long-Wave-Infrared (LWIR) polarimetry are demonstrated with IRCSP. In a room temperature laboratory environment, IRCSP measurements of melting ice are shown to depend on the view angle, wavelength, and thermodynamic phase. As the solid ice melted for 10 minutes, IRCSP measured a constant brightness temperature of 276K between the time-lapsed samples. The difference in the degree of linear polarization (DoLP) between solid and melted ice was 7% on average and peaked at 13% in the 9.5-10.5μm waveband. This observation is an example of enhanced sensitivity to thermodynamic phase change using LWIR polarimetry.

Wildland fire smoke is one of the major sources of biomass-burning aerosols in the Earth’s atmosphere. As the smoke plume evolves, the biomass-burning aerosols undergo aging processes that change their physical and chemical composition. Capturing rapid temporal changes is not suitable for satellites due to the time lapse between observations. Airborne remote sensing offers the ability to increase the spatial and temporal resolution of smoke plume observations compared to satellite observations. However, this increase in spatial and temporal resolution from airborne observations amplifies the need for better spatial coverage from ground-based instruments for validation. In the summer of 2019, the Airborne Multiangle Spectropolarimetric Imager (AirMSPI) was deployed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign on the NASA ER-2 high-altitude research aircraft. This aircraft performed multiple overpasses of the Williams Flats fire near the town of Spokane, Washington, USA, in August 2019, sampling smoke plumes at a georectifed spatial resolution of 10 m². This work performs aerosol retrievals along the smoke plume observed during one flight on 7 August 2019. The retrieval methods used here follow those established by DeLeon et al. (in review) using the Generalized Retrieval of Atmosphere and Surface Properties (GRASP). Two points along the plume were selected: one at 1.35km and the other at 3.78km from the fire source. The fraction of fine mode aerosols and single scattering albedo increased at the greater distance from this wildfire source. These retrieved aerosol properties were used to simulate ground-based polarimetry in ultraviolet, visible, and infrared wavebands. For all wavebands, the maximum degree of linear polarization (DoLP) decreased farther from the source. Notably, the ultraviolet wavebands retained a higher polarimetric signal farther from the source, compared to the visible and infrared. At 865 nm the DoLP decreased from 48.5% to 14.6%. At 355 nm the DoLP decreased from 33.6% to 22.5%. These polarimetric simulations are intended to inform instrument development for ground-based detection of wildfire smoke.

To use moonlight as a source for on-orbit calibration of satellite instruments and for nighttime passive remote sensing, considerable effort has been made to develop and improve radiometric models of the Moon. However, to enable calibration of polarization-sensitive instruments and nighttime polarimetric remote sensing, the polarization state of moonlight must be known as well. While several observations of moonlight polarization have been published, there is no known database of disk-integrated polarization measurements or disk-resolved polarization images as a function of phase angle. We used a monochrome division-of-focal-plane polarization imager with a telescope (focal length of 2 m) and a telephoto lens (focal length of 300 mm) to record images of the degree and angle of linear polarization for lunar phases ranging from full Moon to about 15% full. We calculated the disk-integrated polarization state from the images. We present a plot of disk-integrated polarization state as a function of phase angle, which agrees well with similar plots published previously for small regions of the Moon. The disk-integrated degree of linear polarization (DoLP) reaches a maximum of approximately 8% at a phase angle near 100° and a minimum near 0% at a phase angle of 0°. We also present S₀, DoLP, and angle of polarization (AoP) images and use them to explain the lunar locations where polarized light primarily originates. To our knowledge, the presented DoLP images are higher resolution than previously published DoLP images, and AoP images presented here have not yet been published.

The accuracy of satellite remote sensing of trace gases by imaging spectrometers depends highly on the uniformity of the instrument spectral response function. Studies have shown that scene inhomogeneity across the spectrometer’s slit width (spectral direction) can cause errors in the measured spectral radiances, leading to trace gas retrieval inaccuracy. One mitigation approach recent imaging spectrometers use is a slit homogenizer to redistribute scene radiance within the slit. This on-board hardware device functions like a slab waveguide, with rays making multiple bounces between narrowly spaced, highly reflective, plane-parallel mirrors. This presents a challenge as any difference in s- and p-polarization reflectance for the mirror surfaces tends to multiply with each bounce, producing a net linear polarization sensitivity (LPS) in the system’s throughput which also results in retrieval error. Our solution is a slit homogenizer design that mitigates for LPS by employing total internal reflection (TIR) and a birefringent internal medium. TIR ensures high and equal reflectance while a birefringent material such as sapphire, with an appropriately oriented optic axis, provides high-order retardance between bounces. This introduces polarization scrambling in the manner of a Lyot-depolarizer. We provide a basic analysis of the device’s geometrical optics, detailing the crystalline optic axis orientation for the device cut from a sapphire boule and readily-available R-cut material. Preliminary lab testing was performed on three mirror-pair and two sapphire plate homogenizers at multiple visible wavelengths. The results show that our sapphire plate slit homogenizers decrease LPS by at least an order of magnitude compared to the mirror-based ones.

Object pose estimation is an important problem in the field of remote sensing that provides valuable information for target identification tasks. Polarization is a fundamental property of light that contains useful information about the physical properties of an object, such as shape and surface material properties. Polarization imaging has been shown to have advantages over conventional imaging techniques for object detection and feature extraction in a variety of challenging scenarios, including low light, high background clutter, and low visibility conditions. In this work, we investigate using polarimetric imaging to improve the performance of deep learning approaches to object pose estimation on a range of model target vehicles. We collect polarimetric imaging data and labeled ground truth pose data on the target vehicles in a controlled solar simulation laboratory environment under precise sensor, object, and solar source geometries. We first establish baseline performance of our approach by training our network using conventional visible RGB s0 images under favorable lighting conditions. We then make use of the full linear Stokes images for each color channel in various configurations, retrain our network, and compare performance. We furthermore propose an ensemble method to combine features obtained from convolutional neural networks trained on both conventional RGB and Stokes-vector images. These obtained ensemble features are then used to train a multi-layer perceptron. Experimental results demonstrate that combining polarization imaging with conventional imaging can improve feature extraction and the accuracy of deep learning-based approaches to pose estimation.