Progressive Photon Elimination With a Status Tree

Abstract

We describe a modified progressive photon mapping (PPM) method applied with sample elimination, referred to as progressive photon elimination, to pursue accurate results and accelerated iterations. Meanwhile, an elimination status tree is proposed for progressive photon elimination, which retains the information used in the elimination and can be updated along with the multi-pass process to solve the challenge of the accuracy of local parameters. By using the status tree, our method can obtain a uniform photon distribution at each iteration by eliminating a certain number of photons. The tree is also improved to adapt to the complicated photon distributions. This strategy also facilitates the parallel elimination with a priori elimination ratio in the status tree, making the algorithm further accelerated. In parallel block processing, the equilibrium and edge problems are resolved. The experimental results show that our method requires about half of the number of iterations to achieve the same visual effect compared with progressive photon mapping.

Keywords

• Global illumination
• photon mapping
• sample elimination