Perceptual error optimization for Monte Carlo animation rendering
Creators
- 1. Saarland University, DFKI
- 2. Max Planck Institute for Informatics
- 3. Adobe
- 4. Saarland University
Description
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.
Files
2023_korac_perceptual_zenodo.pdf
Files
(51.7 MB)
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Additional details
Subjects
- Computer Graphics
- https://en.wikipedia.org/wiki/Computer_graphics