Automatic Parameter Control for Metropolis Light Transport

Abstract

Sophisticated global illumination algorithms usually have several control parameters that need to be set appropriately in order to obtain high performance and accuracy. Unfortunately, the optimal values of these parameters are scene dependent, thus their setting is a cumbersome process that requires significant care and is usually based on trial and error. To address this problem, this paper presents a method to automatically control the large step probability parameter of Primary Sample Space Metropolis Light Transport (PSSMLT). The method does not require extra computation time or pre-processing, and runs in parallel with the initial phase of the rendering method. During this phase, it gathers statistics from the process and computes the parameters for the remaining part of the sample generation. We show that the theoretically proposed values are close to the manually found optimum for several complex scenes.