期刊
ACM TRANSACTIONS ON GRAPHICS
卷 34, 期 4, 页码 -出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/2766997
关键词
path tracing; gradient-domain; global illumination; light transport
资金
- Academy of Finland [277833]
- NSF [IIS-1420122]
- Swiss National Science Foundation [143886]
- Helsinki Doctoral Education Network in Information and Communications Technology (HICT)
- Direct For Computer & Info Scie & Enginr
- Div Of Information & Intelligent Systems [1420122] Funding Source: National Science Foundation
- Academy of Finland (AKA) [277833, 277833] Funding Source: Academy of Finland (AKA)
We introduce gradient-domain rendering for Monte Carlo image synthesis. While previous gradient-domain Metropolis Light Transport sought to distribute more samples in areas of high gradients, we show, in contrast, that estimating image gradients is also possible using standard (non-Metropolis) Monte Carlo algorithms, and furthermore, that even without changing the sample distribution, this often leads to significant error reduction. This broadens the applicability of gradient rendering considerably. To gain insight into the conditions under which gradient-domain sampling is beneficial, we present a frequency analysis that compares Monte Carlo sampling of gradients followed by Poisson reconstruction to traditional Monte Carlo sampling. Finally, we describe Gradient-Domain Path Tracing (G-PT), a relatively simple modification of the standard path tracing algorithm that can yield far superior results.
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