{'fraction_non_alphanumeric': 0.022813688212927757, 'fraction_numerical': 0.0009505703422053232, 'mean_word_length': 6.212328767123288, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Surface parameter based image estimation from application of a scattering model to polarized light measurements

An important task for remote sensing applications is the characterization of material properties, which can be accomplished by estimating physics-based parameters from optical scattering off a target’s surface. In this paper, a novel approach is described to generate parameter-based images by applying the modified polarimetric bidirectional reflectance distribution function (pBRDF) model to the polarimetric imaging measurements collected with the University of Arizona’s Ground Multiangle SpectroPolarimetric Imager (Ground-MSPI). Values for complex refractive index (η), slope variance roughness (σ2) and diffuse scattering coefficient (ρd) for each pixel are jointly estimated. Images consisting of the parameter values are generated by using the estimation results and optimized by contrast-ratio enhancement algorithms. The approach offers significant potential for remote targets analysis and novel imaging technology development.