Statistical Characterization of Surface Reflectance

Abstract

The classification of surface reflectance functions as diffuse, specular, and glossy has been introduced by Heckbert more than two decades ago. Many rendering algorithms are dependent on such a classification, as different kinds of light transport will be handled by specialized methods, for example caustics require specular bounce or refraction. Due to the increasing wealth of surface reflectance models including those based on measured data, it has not been possible to keep such a characterization simple. Each surface reflectance model is mostly handled separately, or alternatively, the rendering algorithm restricts itself to the use of some subset of reflectance models. We suggest a characterization for arbitrary surface reflectance representation by standard statistical tools, namely normalized variance known as Squared-Coefficient-of-Variation (SCV). We show by videos that there is even a weak perceptual correspondence with the proposed reflectance characterization, when we use monochromatic surface reflectance and the images are normalized so they have the unit albedo.