Estimating surface orientation from microfacet Mueller matrix bidirectional reflectance distribution function models in outdoor passive imaging polarimetry

Meredith Kupinski,Feng Xu,Russell Chipman,Christine Bradley,David Diner

doi:10.1117/1.oe.58.8.082416

Abstract

Representative examples from 3 years of measurements from JPL’s ground-based multiangle spectropolarimetric imager (GroundMSPI) are compared to a Mueller matrix bidirectional reflectance distribution function (mmBRDF). This mmBRDF is used to model polarized light scattering from solar illuminated surfaces. The camera uses a photoelastic-modulator-based polarimetric imaging technique to measure linear Stokes parameters in three wavebands (470, 660, and 865 nm) with a ±0.005 uncertainty in degree of linear polarization. GroundMSPI measurements are made over a range of scattering angles determined from a fixed viewing geometry and varying sun positions over time. This microfacet mmBRDF model predicts an angle of the linear polarization that is consistently perpendicular to the scattering plane and therefore is only appropriate for rough surface types. The model is comprised of a volumetric reflection term plus a specular reflection term of Fresnel-reflecting microfacets. The following modifications to this mmBRDF model are evaluated: an apodizing shadowing function, a Breon or Gaussian microfacet scattering density function, and treating the surface orientation as an additional model parameter in the specular reflection term. The root-mean-square error (RMSE) between the GroundMSPI measurements and these various forms of the microfacet mmBRDF model is reported. Four example scenes for which a shadowed-Breon microfacet mmBRDF model yields realistic estimates of surface orientation, and the lowest RMSE among other model options are shown.

Highlights

Ground-based sun photometers do not provide adequate spatial or optical sampling to constrain the inverse problem of global aerosol estimation.[1]
We applied modeling methods used in the initial analysis of GroundMSPI measurements[1] to four example datasets collected at the University of Arizona
The microfacet Mueller matrix bidirectional reflectance distribution function (mmBRDF) models for this paper were modified and root-mean-square error (RMSE) comparisons were made for shadowed- and unshadowedGaussian and shadowed- and unshadowed-Bréon scattering density functions

Summary

Introduction

Ground-based sun photometers do not provide adequate spatial or optical sampling to constrain the inverse problem of global aerosol estimation.[1] A downward-looking polarimeter collects light from both the atmosphere and the Earth’s surface and can provide information for spatiotemporal aerosol estimation on a global scale.[2] Many atmospheric imaging studies are conducted over the ocean to avoid optical reflectance from an unknown landscape.[3] The assumption that surface reflection properties are known is not valid for aerosol retrievals over land. If the surface reflection properties are unknown, only multiple-viewing-angle measurements of both intensity and polarization are able to provide the relevant aerosol parameters with sufficient accuracy for climate research.[4,5] Currently, models of atmospheric scattering are more advanced than models of surface reflectance because the polarized light scattering from the Earth’s surface is globally diverse. Semiempirical models are derived from extensive measurements and include a small number of parameters that are fit to measurements.[8,9] To extract the optical and microphysical

Methods

Results

Conclusion