General and Robust Error Estimation and Reconstruction for Monte Carlo Rendering

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dc.contributor.authorBauszat, Pabloen_US
dc.contributor.authorEisemann, Martinen_US
dc.contributor.authorEisemann, Elmaren_US
dc.contributor.authorMagnor, Marcusen_US
dc.contributor.editorOlga Sorkine-Hornung and Michael Wimmeren_US
dc.date.accessioned2015-04-16T07:46:13Z
dc.date.available2015-04-16T07:46:13Z
dc.date.issued2015en_US
dc.description.abstractAdaptive filtering techniques have proven successful in handling non-uniform noise in Monte-Carlo rendering approaches. A recent trend is to choose an optimal filter per pixel from a selection of non spatially-varying filters. Nonetheless, the best filter choice is difficult to predict in the absence of a reference rendering. Our approach relies on the observation that the reconstruction error is locally smooth for a given filter. Hence, we propose to construct a dense error prediction from a small set of sparse but robust estimates. The filter selection is then formulated as a non-local optimization problem, which we solve via graph cuts, to avoid visual artifacts due to inconsistent filter choices. Our approach does not impose any restrictions on the used filters, outperforms previous state-of-the-art techniques and provides an extensible framework for future reconstruction techniques.en_US
dc.description.number2en_US
dc.description.sectionheadersGlobal Illuminationen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume34en_US
dc.identifier.doi10.1111/cgf.12587en_US
dc.identifier.pages597-608en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12587en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.3.7 [Computer Graphics]en_US
dc.subjectThree Dimensional Graphics and Realismen_US
dc.subjectRaytracingen_US
dc.titleGeneral and Robust Error Estimation and Reconstruction for Monte Carlo Renderingen_US
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