Weighted Importance Sampling in Shooting Algorithms

Balázs Benedek, László Szirmay-Kalos, Antal György
Department of Control Engineering and Information Technology, Technical University of Budapest,
Budapest, Magyar Tudósok krt. 2, H-1117, HUNGARY


This paper proposes the application of a variance reduction technique called weighted importance sampling in shooting type global illumination algorithms. The sampling applied by shooting type Monte-Carlo global illumination algorithms can mimic the power of the transfer, but not the BRDFs at the visible target. Consequently, these algorithms are poor in rendering visible specular surfaces. In order to eliminate these drawbacks, the BRDFs at the visible targets are taken into account as an additional weighting of the sampling density. After discussing the basic concepts we demonstrate the proposed idea with two algorithms. The first one uses conventional rays, while the second one ray-bundles to transfer the light in the scene.