Anisotropic Kuwahara Filtering with Polynomial Weighting Functions

dc.contributor.authorKyprianidis, Jan Ericen_US
dc.contributor.authorSemmo, Amiren_US
dc.contributor.authorKang, Henryen_US
dc.contributor.authorDöllner, Jürgenen_US
dc.contributor.editorJohn Collomosse and Ian Grimsteaden_US
dc.date.accessioned2014-01-31T20:11:51Z
dc.date.available2014-01-31T20:11:51Z
dc.date.issued2010en_US
dc.description.abstractIn this work we present new weighting functions for the anisotropic Kuwahara filter. The anisotropic Kuwahara filter is an edge-preserving filter that is especially useful for creating stylized abstractions from images or videos. It is based on a generalization of the Kuwahara filter that is adapted to the local shape of features. For the smoothing process, the anisotropic Kuwahara filter uses weighting functions that use convolution in their definition. For an efficient implementation, these weighting functions are usually sampled into a texture map. By contrast, our new weighting functions do not require convolution and can be efficiently computed directly during the filtering in real-time. We show that our approach creates output of similar quality as the original anisotropic Kuwahara filter and present an evaluation scheme to compute the new weighting functions efficiently by using rotational symmetries.en_US
dc.description.seriesinformationTheory and Practice of Computer Graphicsen_US
dc.identifier.isbn978-3-905673-75-3en_US
dc.identifier.urihttps://doi.org/10.2312/LocalChapterEvents/TPCG/TPCG10/025-030en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.3 [Picture/Image Generation]: Display algorithmsen_US
dc.titleAnisotropic Kuwahara Filtering with Polynomial Weighting Functionsen_US
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