Real-Time Importance Sampling of Dynamic Environment Maps

Abstract

We introduce a simple and effective technique for light-based importance sampling of dynamic environment maps based on the formalism of Multiple Importance Sampling (MIS). The core idea is to balance per pixel the number of samples selected on each cube map face according to a quick and conservative evaluation of the lighting contribution: this increases the number of effective samples. In order to be suitable for dynamically generated or captured HDR environment maps, everything is computed on-line for each frame without any global preprocessing. Our results illustrate that the low number of required samples combined with a full-GPU implementation lead to real-time performance with improved visual quality. Finally, we illustrate that our MIS formalism can be easily extended to other strategies such as BRDF importance sampling.