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Journal of Electronic Imaging

Blue noise sampling method based on mixture distance
Author(s): Hongxing Qin; XiaoYang Hong; Bin Xiao; Shaoting Zhang; Guoyin Wang
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Paper Abstract

Blue noise sampling is a core component for a large number of computer graphic applications such as imaging, modeling, animation, and rendering. However, most existing methods are concentrated on preserving spatial domain properties like density and anisotropy, while ignoring feature preserving. In order to solve the problem, we present a new distance metric called mixture distance for blue noise sampling, which is a combination of geodesic and feature distances. Based on mixture distance, the blue noise property and features can be preserved by controlling the ratio of the geodesic distance to the feature distance. With the intention of meeting different requirements from various applications, an adaptive adjustment for parameters is also proposed to achieve a balance between the preservation of features and spatial properties. Finally, implementation on a graphic processing unit is introduced to improve the efficiency of computation. The efficacy of the method is demonstrated by the results of image stippling, surface sampling, and remeshing.

Paper Details

Date Published: 16 December 2014
PDF: 13 pages
J. Electron. Imag. 23(6) 063015 doi: 10.1117/1.JEI.23.6.063015
Published in: Journal of Electronic Imaging Volume 23, Issue 6
Show Author Affiliations
Hongxing Qin, Chongqing Univ. of Posts and Telecommunications (China)
Chongqing Key Lab. of Computational Intelligence (China)
XiaoYang Hong, Chongqing Univ. of Posts and Telecommunications (China)
Bin Xiao, Chongqing Univ. of Posts and Telecommunications (China)
Shaoting Zhang, The Univ. of North Carolina at Charlotte (United States)
Guoyin Wang, Chongqing Univ. of Posts and Telecommunications (China)

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