期刊
ACM TRANSACTIONS ON GRAPHICS
卷 32, 期 1, 页码 -出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/2421636.2421643
关键词
Algorithms; Theory; Photon mapping; blue noise; photon relaxation; global illumination
资金
- Wales Research Institute of Visual Computing
- EPSRC [EP/I031243/1]
- Engineering and Physical Sciences Research Council [EP/I031243/1] Funding Source: researchfish
We introduce a novel algorithm for progressively removing noise from view-independent photon maps while simultaneously minimizing residual bias. Our method refines a primal set of photons using data from multiple successive passes to estimate the incident flux local to each photon. We show how this information can be used to guide a relaxation step with the goal of enforcing a constant, per-photon flux. Using a reformulation of the radiance estimate, we demonstrate how the resulting blue noise photon distribution yields a radiance reconstruction in which error is significantly reduced. Our approach has an open-ended runtime of the same order as unbiased and asymptotically consistent rendering methods, converging over time to a stable result. We demonstrate its effectiveness at storing caustic illumination within a view-independent framework and at a fidelity visually comparable to reference images rendered using progressive photon mapping.
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