Statistical Characterization of Surface Reflectance (English)

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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.

Table of contents conference proceedings

The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.

Reducing Anisotropic BSDF Measurement to Common Practice
Ward, Greg / Kurt, Murat / Bonneel, Nicolas | 2014
Linear Transport Theory and Applications to Rendering
Jakob, Wenzel | 2014
Scanning Gonio-Photometers for Asymmetric Acquisition of Fine-structured BSDF
Apian-Bennewitz, Peter | 2014
Statistical Characterization of Surface Reflectance
Havran, Vlastimil / Sbert, Mateu | 2014
The Role of Visual Comparison Testing in Material Appearance Modeling
Meyer, Gary | 2014
The MAM2014 Sample Set
Rushmeier, Holly | 2014
ALTA: A BRDF Analysis Library
Belcour, Laurent / Barla, Pascal / Pacanowski, Romain | 2014