An Empirical Comparison of Progressive and Wavelet Radiosity

Abstract

This paper presents a comparison of basic progressive and wavelet radiosity algorithms. Several variants of each algorithm were run on a set of scenes at several parameter settings, and results were examined in terms of their error, speed, and memory consumption. We did not compare more advanced variations such as clustering or discontinuity meshing. Our results show that progressive radiosity with substructuring works fairly well for all scenes. Among wavelet methods, the Haar basis works best, while higher order methods suffer because of extreme memory consumption and because poor visibility handling causes discontinuous, blocky shadows.