Irradiance regression for efficient final gathering in global illumination

Abstract

Photon mapping is widely used for global illumination rendering because of its high computational efficiency. But its efficiency is still limited mainly by the intensive sampling required in final gathering a process that is critical for removing low frequency artifacts of density estimation. In this paper we propose a method to predict the final gathering estimation with direct density estimation thereby achieving high quality global illumination by photon mapping with high efficiency. We first sample the irradiance of a subset of shading points by both final gathering and direct radiance estimation. Then we use the samples as a training set to predict the final gathered irradiance of other shading points through regression. Consequently we are able to achieve about three times overall speedup compared with straightforward final gathering in global illumination computation with the same rendering quality.