Fast High-Dimensional Filtering Using the Permutohedral Lattice

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dc.contributor.authorAdams, Andrewen_US
dc.contributor.authorBaek, Jongminen_US
dc.contributor.authorDavis, Myers Abrahamen_US
dc.date.accessioned2015-02-23T16:42:59Z
dc.date.available2015-02-23T16:42:59Z
dc.date.issued2010en_US
dc.description.abstractMany useful algorithms for processing images and geometry fall under the general framework of high-dimensional Gaussian filtering. This family of algorithms includes bilateral filtering and non-local means. We propose a new way to perform such filters using the permutohedral lattice, which tessellates high-dimensional space with uniform simplices. Our algorithm is the first implementation of a high-dimensional Gaussian filter that is both linear in input size and polynomial in dimensionality. Furthermore it is parameter-free, apart from the filter size, and achieves a consistently high accuracy relative to ground truth (> 45 dB). We use this to demonstrate a number of interactive-rate applications of filters in as high as eight dimensions.en_US
dc.description.number2en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume29en_US
dc.identifier.doi10.1111/j.1467-8659.2009.01645.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages753-762en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2009.01645.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltden_US
dc.titleFast High-Dimensional Filtering Using the Permutohedral Latticeen_US
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