Combined Correlated and Importance Sampling in Direct Light Source Computation and Environment Mapping

Szécsi László, Mateu Sbert, Szirmay-Kalos László
Department of Control Engineering and Information Technology, Budapest, University of Technology,
Budapest, Magyar Tudósok krt. 2, H-1117, HUNGARY


This paper presents a general variance reduction method that is a quasi-optimal combination of correlated and importance sampling. The weights of the combination are selected automatically in order to keep the merits of both importance and correlated sampling. The proposed sampling method is used for efficient direct light source computation of large area sources and for the calculation of the reflected illumination of environment maps. Importance sampling would be good in these cases if the sources are hidden, while correlated sampling is efficient if the sources are fully visible. The proposed method automatically detects the particular case and provides results that inherit the advantages of both techniques. Keywords: