Unbiased photon gathering for light transport simulation

Abstract

Photon mapping (PM) has been widely regarded as an efficient solution for light transport simulation, including challenging caustics paths and many-bounce indirect lighting. The efficiency of PM comes from reusing traced photons. However, the handling of photon gathering in existing PM algorithms is universally biased -- the expected value of their results does not necessarily agree with the true solution of the rendering equation. We present a novel photon gathering method to efficiently achieve unbiased rendering with photon mapping. Instead of aggregating the gathered photons into an estimated density as in classical photon mapping, we process each photon individually and connect the corresponding light sub-path with the eye sub-path that generates the gather point, creating an unbiased path sample. The Monte Carlo estimate for such a path sample is calculated by evaluating all relevant terms in a strict and unbiased way, leading to a self-contained unbiased sampling technique. We further develop a set of multiple importance sampling (MIS) weights that allow our method to be optimally combined with bidirectional path tracing (BDPT), resulting in an unbiased rendering algorithm that can efficiently handle a wide variety of light paths and that compares favorably with previous algorithms. Experiments demonstrate the efficacy and robustness of our method.