Independently estimating pixel values in Monte Carlo rendering results in a perceptually sub-optimal white-noise distribution of error in image space. Recent works have shown that perceptual fidelity can be improved significantly by distributing pixel error as blue noise instead. Most such works have focused on static images, ignoring the temporal perceptual effects of animation display. We extend prior formulations to simultaneously consider the spatial and temporal domains, and perform an analysis to motivate a perceptually better spatio-temporal error distribution. We then propose a practical error optimization algorithm for spatio-temporal rendering and demonstrate its effectiveness in various configurations.
Note that video takes time to download as it is fairly large. This is due to less aggressive video compression encoding, which had to be used in order to keep noise visible.
@inproceedings{Korac:2023:PerceptualErrorOptimizationAnimation,
author = {Mi\v{s}a Kora\'{c} and Corentin Sala\"{u}n and Iliyan Georgiev and Pascal Grittmann and Philipp Slusallek and Karol Myszkowski and Gurprit Singh},
title = {Perceptual error optimization for Monte Carlo animation rendering},
booktitle = {ACM SIGGRAPH Asia 2023 Conference Proceedings},
year = {2023},
doi = {10.1145/3610548.3618146},
isbn = {979-8-4007-0315-7/23/12}
}