An Effective Stratified Sampling Scheme for Environment Maps with Median Cut Method

Abstract

Environment maps are extensively used as natural light sources in realistic rendering. We propose a stratified sampling scheme for environment maps by first stratifying the maps into a set of rectangular regions with median cut method, then estimating the contribution of the regions with Monte Carlo integration techniques. In this way, illumination, surface reflectance and spatial distribution are all taken into consideration for the generation of the light samples. Compared with the existing biased lighting techniques, the presented scheme produces unbiased rendering results with less noise and better shadow boundaries, particularly at low sampling rates. The proposed spatial distribution of the samples also helps to overcome the sample-clumping problem in traditional illumination-based importance sampling method. Experimental results indicate that the scheme is fast, simple to implement and effective