Authors:
Rosana Montes
;
Carlos Ureña
;
Rubén García
and
Miguel Lastra
Affiliation:
E.T.S.I. Informática y de Telecomunicación, University of Granada, Spain
Keyword(s):
BRDF, Importance Sampling, Monte Carlo Integration, Global Illumination, Rendering, Path Tracing.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Lighting and Appearance
;
Rendering
;
Rendering Algorithms
Abstract:
This paper introduces a new BRDF sampling method with reduced variance, which is based on a hierarchical adaptive parameterless PDF. This PDF is based also on rejection sampling with a bounded average number of trials, even in regions where the BRDF does exhibit high variations. Our algorithm works in an appropiate way with both physical and analytical reflectance models. Reflected directions are sampled by using importance sampling of the BRDF times the cosine term. This fact improves computation of reflected radiance when Monte-Carlo integration is used in Global Illumination. Test images have been obtained by using a Monte- Carlo rendering system, and they show reduced variance as compared with those obtained by other known techniques.