Overview of BSDF Reconstruction Methods for Rough Surfaces

Abstract

The work provides an overview of methods aimed to the reconstruction of Bidirectional Scattering Distribution Function (BSDF) for rough surfaces. The elements with rough surfaces are permanently present in our life and widely used in modern optical devices, for exam-ple, in light guiding plates for display illuminating systems, car dashboards, or luminaires. Light scattering by rough surface is an important component in the visual appearance of many materials including water, glass, skin, etc. The problem of the rough surface visualization is complex and contains many different aspects. Accordingly there are many techniques to provide their realistic rendering. In many lighting simulation and optical design tasks it is sufficient and more effective to replace real geometry of rough surface by a surface optical characteristics expressed via BSDF. So, accurate reconstruction of scattering properties of rough surfaces is a significant factor in visualizations tasks and generation of photorealistic images. In some cases, BSDF can be just measured. However, in many cases direct BSDF measurements are impossible if, for example, it is required to define BSDF inside of the material and neither a measuring device detector nor a light source can be placed inside the material. So this results in the development of many approaches for BSDF reconstruction. It started in the end of the last century with the development of many analytical methods based on microfacet models of rough surface such as the Phong, the Ward reflection, the Cook-Torrance models. Nowadays many direct numerical methods of BSDF reconstruction appear, for example, methods based on normals and heights distribution. As a rule, these methods use ray tracing to calculate BSDF. Sizes of microroughness can be small, sufficient to raise a problem which optics wave or ray is more appropriate here. To answer this and other ques-tions related to BSDF reconstruction, an investigation of well-known and effective reconstruct methods was conducted. This paper also presents the study results for eight real samples with different profile parameters of rough surface. The verification is based on numerical comparison with real measured data and visual comparison of images generated using different reconstructed BSDF. Finally, the general recommendations are presented about what methods and for what applications are more appropriate.