Abstract
Rendering with global illumination has been used mainly in the field of film production, architecture, and design due to its highly photorealistic image synthesis. When using Monte Carlo raytracing, which is one of the major rendering methods, the resulting images may contain some points that deviate significantly from final convergence values. An optimization method is needed to generate output images with a small number of samples and low variance by improving the dispersion reduction per sample. Path guiding is a method for reducing such dispersion by using importance sampling of the estimated radiance distribution in advance to construct efficient paths. However, in many-light scenes, estimating radiance distribution may be slow due to the complexity of distribution obtained by the light sources and it could make dispersion rather increased by constructing paths from the trained distribution of low accuracy. In this article, therefore, we propose a method for improving the computational efficiency of path guiding with many-light global illumination by sophisticating light source sampling to improve the estimation of radiance distribution. The proposed method was implemented as a GPU program, and we empirically proved that it reduced up to 41.4 % of dispersion compared to the normal path tracing.
