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Presentation

Screen-Space Blue-Noise Diffusion of Monte Carlo Sampling Error via Hierarchical Ordering of Pixels
Event Type
Technical Papers
Technical Papers Q&A
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TimeFriday, 11 December 202010:12 - 10:18 SGT
LocationZoom Room 2
DescriptionWe present a novel technique for diffusing Monte Carlo sampling error as a blue noise in screen space.
We show that automatic diffusion of sampling error can be achieved by ordering the pixels in a way that preserves locality, such as Z-ordering, and assigning the samples to them from successive sub-sequences of a single low-discrepancy sequence, thus securing well-distributed samples for each pixel, local neighborhoods, and the hole image.
We further show that a blue-noise distribution of the error is attainable by scrambling the Z-ordering to induce isotropy.
We present an efficient technique to implement this hierarchical scrambling by defining a context-free grammar that describes infinite self-similar lookup trees.
Our concept is scalable to arbitrary image resolutions, sample dimensions, and sample count, and supports progressive and adaptive sampling.