Parallel Blue-noise Sampling by Constrained Farthest Point Optimization

We 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 tradeo...

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Vydané v:Computer graphics forum Ročník 31; číslo 5; s. 1775 - 1785
Hlavní autori: Chen, Renjie, Gotsman, Craig
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford, UK Blackwell Publishing Ltd 01.08.2012
Predmet:
Algorithms
Computation
Computer graphics
Constraints
I.3.3 [Computer Graphics]: Picture/Image Generation
I.4.1 [Image Processing and Computer Vision]: Digitization and Image Capture-Sampling
Noise
Optimization
Parallel processing
Sampling
State of the art
Studies
ISSN:0167-7055, 1467-8659
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Popis
Shrnutí:We 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‐the‐art approaches.
Bibliografia:ArticleID:CGF3182
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SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ObjectType-Article-2
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ISSN:0167-7055
1467-8659
DOI:10.1111/j.1467-8659.2012.03182.x