Denoising your Monte Carlo renders
Pradeep K. Sen, Matthias Zwicker, Fabrice Rousselle, Sung‐Eui Yoon, Nima Khademi Kalantari · 2015
Monte Carlo integration is firmly established as the basis for most practical realistic image synthesis algorithms because of its flexibility and generality. However, the visual quality of rendered images often suffers from estimator variance, which appears as visually distracting noise. The current shift in the computer graphics industry towards Monte Carlo rendering has sparked renewed interest in effective, practical noise reduction techniques that are applicable to a wide range of rendering effects, and easily integrated into existing production pipelines.