Datensatz

Zusammenfassung

Photon mapping is one of the most important algorithms for computing global illumination. Especially for effi- ciently producing convincing caustics, there are no real alternatives to photon mapping. On the other hand, photon mapping is also quite costly: Each radiance lookup requires to find the k nearest neighbors in a kd-tree, which can be more costly than shooting several rays. Therefore, the nearest-neighbor queries often dominate the rendering time of a photon map based renderer. In this paper, we present a method that reorganizes i.e. unbalances the kd-tree for storing the photons in a way that allows for finding the k-nearest neighbors much more efficiently, thereby accelerating the radiance estimates by a factor of 1.2 3.4. Most importantly, our method still finds exactly the same k-nearest-neighbors as the original method, without introducing any approximations or loss of accuracy. The impact of our method is demonstrated with several practical examples.