Deterministic Importance Sampling with Error Diffusion

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dc.contributor.authorSzirmay-Kalos, Laszloen_US
dc.contributor.authorSzecsi, Laszloen_US
dc.date.accessioned2015-02-23T14:55:33Z
dc.date.available2015-02-23T14:55:33Z
dc.date.issued2009en_US
dc.description.abstractThis paper proposes a deterministic importance sampling algorithm that is based on the recognition that delta-sigma modulation is equivalent to importance sampling. We propose a generalization for delta-sigma modulation in arbitrary dimensions, taking care of the curse of dimensionality as well. Unlike previous sampling techniques that transform low-discrepancy and highly stratified samples in the unit cube to the integration domain, our error diffusion sampler ensures the proper distribution and stratification directly in the integration domain. We also present applications, including environment mapping and global illumination rendering with virtual point sources.en_US
dc.description.number4en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume28en_US
dc.identifier.doi10.1111/j.1467-8659.2009.01482.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages1055-1064en_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/CGF.v28i4pp1055-1064en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2009.01482.xen_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/CGF.v28i4pp1055-1064
dc.publisherThe Eurographics Association and Blackwell Publishing Ltden_US
dc.titleDeterministic Importance Sampling with Error Diffusionen_US
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EGSR09: 20th Eurographics Symposium on Rendering