Screen-space blue-noise diffusion of monte carlo sampling error via hierarchical ordering of pixels

Abdalla G. M. Ahmed, Peter Wonka

Research output: Contribution to journalArticlepeer-review

Abstract

We 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 Morton's Z-ordering, and assigning the samples to the pixels from successive sub-sequences of a single low-discrepancy sequence, thus securing well-distributed samples for each pixel, local neighborhoods, and the whole 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.
Original languageEnglish (US)
Pages (from-to)1-15
Number of pages15
JournalACM Transactions on Graphics
Volume39
Issue number6
DOIs
StatePublished - Nov 26 2020

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