Data-driven Algorithm to Classify the Degree of Isotropy in the Bidirectional Reflectance Distribution Function
The bidirectional reflectance distribution function (BRDF) is used to describe reflectances of materials by calculating the ratio of the reflected radiance to the incident irradiance. While it was found that the isotropic models maintained symmetry about ϕs = π, such symmetry was not maintained about the θs = θi axis, except for close to the specular peak. This led to the development of a data-driven metric for how isotropic a BRDF measurement is. Research efforts centered around developing an algorithm that could determine material anisotropy without having to fit to models. This algorithm was tested using high fidelity data (containing off-axis BRDFs), which was collected via a modified Complete Angle Scatter Instrument (CASI®) with a CCD array detector. The algorithm accurately characterized the degree of isotropy for four out of five materials and worked for cases where the BRDF is higher than 100 sr −1. This algorithm is intended to improve BRDF characterization, and the applications of light curve analysis, scene generation, and remote sensing.
Anne W. Werkley, Samuel D. Butler, Todd V. Small, and Michael A. Marciniak "Data-driven algorithm to classify the degree of isotropy in the bidirectional reflectance distribution function," Optical Engineering 60(9), 094108 (20 September 2021). https://doi.org/10.1117/1.OE.60.9.094108
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