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Article: Variational blue noise sampling

TitleVariational blue noise sampling
Authors
KeywordsBlue noise
Capacity-constrained
Centroidal voronoi tessellation
Point sampling
Quasi-newton method
Issue Date2012
PublisherIEEE. The Journal's web site is located at http://www.computer.org/tvcg
Citation
IEEE Transactions on Visualization and Computer Graphics, 2012, v. 18 n. 10, p. 1784-1796 How to Cite?
AbstractBlue noise point sampling is one of the core algorithms in computer graphics. In this paper, we present a new and versatile variational framework for generating point distributions with high-quality blue noise characteristics while precisely adapting to given density functions. Different from previous approaches based on discrete settings of capacity-constrained Voronoi tessellation, we cast the blue noise sampling generation as a variational problem with continuous settings. Based on an accurate evaluation of the gradient of an energy function, an efficient optimization is developed which delivers significantly faster performance than the previous optimization-based methods. Our framework can easily be extended to generating blue noise point samples on manifold surfaces and for multi-class sampling. The optimization formulation also allows us to naturally deal with dynamic domains, such as deformable surfaces, and to yield blue noise samplings with temporal coherence. We present experimental results to validate the efficacy of our variational framework. Finally, we show a variety of applications of the proposed methods, including nonphotorealistic image stippling, color stippling, and blue noise sampling on deformable surfaces. © 1995-2012 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/165853
ISSN
2015 Impact Factor: 1.4
2015 SCImago Journal Rankings: 0.917
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChen, Zen_US
dc.contributor.authorYuan, Zen_US
dc.contributor.authorChoi, YKen_US
dc.contributor.authorLiu, Len_US
dc.contributor.authorWang, Wen_US
dc.date.accessioned2012-09-20T08:24:33Z-
dc.date.available2012-09-20T08:24:33Z-
dc.date.issued2012en_US
dc.identifier.citationIEEE Transactions on Visualization and Computer Graphics, 2012, v. 18 n. 10, p. 1784-1796en_US
dc.identifier.issn1077-2626-
dc.identifier.urihttp://hdl.handle.net/10722/165853-
dc.description.abstractBlue noise point sampling is one of the core algorithms in computer graphics. In this paper, we present a new and versatile variational framework for generating point distributions with high-quality blue noise characteristics while precisely adapting to given density functions. Different from previous approaches based on discrete settings of capacity-constrained Voronoi tessellation, we cast the blue noise sampling generation as a variational problem with continuous settings. Based on an accurate evaluation of the gradient of an energy function, an efficient optimization is developed which delivers significantly faster performance than the previous optimization-based methods. Our framework can easily be extended to generating blue noise point samples on manifold surfaces and for multi-class sampling. The optimization formulation also allows us to naturally deal with dynamic domains, such as deformable surfaces, and to yield blue noise samplings with temporal coherence. We present experimental results to validate the efficacy of our variational framework. Finally, we show a variety of applications of the proposed methods, including nonphotorealistic image stippling, color stippling, and blue noise sampling on deformable surfaces. © 1995-2012 IEEE.-
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://www.computer.org/tvcg-
dc.relation.ispartofIEEE Transactions on Visualization and Computer Graphicsen_US
dc.rightsIEEE Transactions on Visualization and Computer Graphics. Copyright © IEEE-
dc.rights©2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectBlue noise-
dc.subjectCapacity-constrained-
dc.subjectCentroidal voronoi tessellation-
dc.subjectPoint sampling-
dc.subjectQuasi-newton method-
dc.titleVariational blue noise samplingen_US
dc.typeArticleen_US
dc.identifier.emailYuan, Z: zyuan@cs.hku.hk.en_US
dc.identifier.emailChoi, YK: lykchoi@hku.hken_US
dc.identifier.emailWang, W: wenping@cs.hku.hk-
dc.identifier.authorityChoi, YK=rp00106en_US
dc.identifier.authorityWang, W=rp00186en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/TVCG.2012.94-
dc.identifier.pmid22566473-
dc.identifier.scopuseid_2-s2.0-84865380897-
dc.identifier.hkuros208988en_US
dc.identifier.volume18en_US
dc.identifier.issue10-
dc.identifier.spage1784en_US
dc.identifier.epage1796en_US
dc.identifier.isiWOS:000307298800017-
dc.publisher.placeUnited States-
dc.customcontrol.immutablejt 130328-

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