Abstract
Photon mapping is a widely used technique for global illumination rendering. In the density estimation step of photon mapping, the indirect radiance at a shading point is estimated through a filtering process using nearby stored photons; an isotropic filtering kernel is usually used. However, using an isotropic kernel is not always the optimal choice, especially for cases when eye paths intersect with surfaces with anisotropic BRDFs. In this paper, we propose an anisotropic filtering kernel for density estimation to handle such anisotropic eye paths. The anisotropic filtering kernel is derived from the recently introduced anisotropic spherical Gaussian representation of BRDFs. Compared to conventional photon mapping, our method is able to reduce rendering errors with negligible additional cost when rendering scenes containing anisotropic BRDFs.
Highlights
Global illumination is a long and important research direction in computer graphics
Since density estimation can only be applied on diffuse surfaces, eye rays towards surfaces with anisotropic BRDFs need further tracing in the scene until hitting a diffuse surface
Anisotropic filtering is only applied to density estimation for anisotropic eye paths
Summary
Global illumination is a long and important research direction in computer graphics. Photon mapping [1, 2] has always been a widely used technique for global illumination due to its high rendering quality and good efficiency. We focus on using photon mapping to render scenes with anisotropic BRDFs. Since density estimation can only be applied on diffuse surfaces, eye rays towards surfaces with anisotropic BRDFs need further tracing in the scene until hitting a diffuse surface. One exception is photon differentials [7, 8] They use an anisotropic filtering kernel for density estimation derived from ray differentials stored in photons, and it is effective in reducing bias when rendering caustics. They only take into consideration of the information in light paths but not eye paths in constructing filtering kernel, they will not be beneficial to render anisotropic eye paths. Our experiments demonstrate that our anisotropic kernel yields a better accuracy in rendering anisotropic scenes without incurring additional rendering costs
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