Material characterization by inverse rendering

The optical characterization of materials is crucial for understanding their fundamental properties and potential applications in various fields, including electronics, photonics, and materials science. In this contribution, we present a novel approach for material characterization through inverse rendering, focusing on the approximation of the bidirectional reflectance distribution function (BRDF). The BRDF is characterized by its dependence on various factors, including surface texture, material composition, and wavelength of light, making it a complex but vital tool for predicting how surfaces will appear under different lighting conditions. Using computational imaging and optimized illumination patterns, our method significantly enhances the efficiency of BRFD estimation compared to traditional mechanical scanning techniques. This advancement could be beneficial for practical applications in fields such as material identification and computer graphics, but also opens avenues for future research in automated visual inspection.