Ray maps for global illumination

Abstract

We describe a novel data structure for representing light transport called ray map. The ray map extends the concept of photon maps: it stores not only photon impacts but the whole photon paths. We demonstrate the utility of ray maps for global illumination by eliminating boundary bias and reducing topological bias of density estimation in global illumination. Thanks to the elimination of boundary bias we could use ray maps for fast direct visualization with the image quality being close to that obtained by the expensive final gathering step. We describe in detail our implementation of the ray map using a lazily constructed kD-tree. We also present several optimizations bringing the ray map query performance close to the performance of the photon map.