Bochang Moon
Noise Reduction on G-Buffers for Monte Carlo Filtering: Noise Reduction on G-Buffers for Monte Carlo Filtering
Moon, Bochang; Iglesias-Guitian, Jose A.; McDonagh, Steven; Mitchell, Kenny
Authors
Abstract
We propose a novel pre-filtering method that reduces the noise introduced by depth-of-field and motion blur effects in geometric
buffers (G-buffers) such as texture, normal and depth images. Our pre-filtering uses world positions and their variances to
effectively remove high-frequency noise while carefully preserving high-frequency edges in the G-buffers. We design a new
anisotropic filter based on a per-pixel covariance matrix of world position samples. A general error estimator, Stein’s unbiased
risk estimator, is then applied to estimate the optimal trade-off between the bias and variance of pre-filtered results. We have
demonstrated that our pre-filtering improves the results of existing filtering methods numerically and visually for challenging
scenes where depth-of-field and motion blurring introduce a significant amount of noise in the G-buffers.
Citation
Moon, B., Iglesias-Guitian, J. A., McDonagh, S., & Mitchell, K. (2017). Noise Reduction on G-Buffers for Monte Carlo Filtering: Noise Reduction on G-Buffers for Monte Carlo Filtering. Computer Graphics Forum, 36(8), 600-612. https://doi.org/10.1111/cgf.13155
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 12, 2016 |
Online Publication Date | May 23, 2017 |
Publication Date | May 23, 2017 |
Deposit Date | Jun 23, 2017 |
Journal | Computer Graphics Forum |
Print ISSN | 0167-7055 |
Electronic ISSN | 1467-8659 |
Publisher | Wiley |
Peer Reviewed | Peer Reviewed |
Volume | 36 |
Issue | 8 |
Pages | 600-612 |
DOI | https://doi.org/10.1111/cgf.13155 |
Keywords | Image filtering, denoising, Monte Carlo ray tracing, |
Public URL | http://researchrepository.napier.ac.uk/Output/951658 |
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