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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Bibliographic Details
Published in:Computer graphics forum Vol. 31; no. 5; pp. 1775 - 1785
Main Authors: Chen, Renjie, Gotsman, Craig
Format: Journal Article
Language:English
Published: Oxford, UK Blackwell Publishing Ltd 01.08.2012
Subjects:
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
Online Access:Get full text
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Summary: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.
Bibliography:ArticleID:CGF3182
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ISSN:0167-7055
1467-8659
DOI:10.1111/j.1467-8659.2012.03182.x