Progressive photon mapping with sample elimination

Abstract

Progressive photon mapping [Hachisuka et al. 2008] (PPM) obtains increasingly accurate results with progressive visualization, but it is problematic when results are obtained through thousands of iterations. An uniform photon distribution is critical for the accurate result. In this work, we use the sample elimination [Yuksel 2015] (SE) in PPM to achieve optimal results and accelerate the iterations. Sample elimination can produce sample sets with more pronounced blue noise characteristics. We apply the feature of this elimination method to the progressive iterations.