Parallel Blue-noise Sampling by Constrained Farthest Point Optimization

Simple item page
dc.contributor.authorChen, Renjieen_US
dc.contributor.authorGotsman, Craigen_US
dc.contributor.editorEitan Grinspun and Niloy Mitraen_US
dc.date.accessioned2015-02-28T07:44:17Z
dc.date.available2015-02-28T07:44:17Z
dc.date.issued2012en_US
dc.description.abstractWe describe a fast sampling algorithm for generating uniformly-distributed point patterns with good blue noise characteristics. The method, based on constrained farthest point optimization, is provably optimal and may be easily parallelized, resulting in an algorithm whose performance/quality tradeoff is superior to other state-of-theart approaches.en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume31
dc.identifier.doi10.1111/j.1467-8659.2012.03182.x
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2012.03182.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.subjectI.3.3 [Computer Graphics]en_US
dc.subjectPicture/Image Generationen_US
dc.subjectI.4.1 [Image Processing and Computer Vision]en_US
dc.subjectDigitization and Image Captureen_US
dc.subjectSamplingen_US
dc.titleParallel Blue-noise Sampling by Constrained Farthest Point Optimizationen_US
Files
Collections
31-Issue 5
SGP12: Eurographics Symposium on Geometry Processing