A NEW COMPUTATIONAL WAY TO MONTE CARLO GLOBAL ILLUMINATION

Abstract

In this paper, we present a new Monte Carlo computational way for solving the global illumination problem whereby plenty of unbiased estimators can be employed to enrich the solutions leading to simple error control and faster estimation. Especially so, the zero variance importance sampling procedure can be exploited to calculate the global illumination optimally. Based on the new scheme, a new Monte Carlo global illumination algorithm and its importance driven version have been developed and carried out. Results, which have been obtained by rendering test scenes, show that this new framework is promising.