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Article: Data-driven image color theme enhancement

TitleData-driven image color theme enhancement
Authors
Keywordscolor optimization
color theme
histograms
soft segmentation
texture classes
Issue Date2010
PublisherAssociation for Computing Machinery, Inc.
Citation
ACM Transactions On Graphics, 2010, v. 29 n. 6, article no. 146 How to Cite?
AbstractIt is often important for designers and photographers to convey or enhance desired color themes in their work. A color theme is typically defined as a template of colors and an associated verbal description. This paper presents a data-driven method for enhancing a desired color theme in an image. We formulate our goal as a unified optimization that simultaneously considers a desired color theme, texture-color relationships as well as automatic or user-specified color constraints. Quantifying the difference between an image and a color theme is made possible by color mood spaces and a generalization of an additivity relationship for two-color combinations. We incorporate prior knowledge, such as texture-color relationships, extracted from a database of photographs to maintain a natural look of the edited images. Experiments and a user study have confirmed the effectiveness of our method. © 2010 ACM.
DescriptionProceedings of the 3rd ACM SIGGRAPH Asia 2010, Seoul, South Korea, 15-18 December 2010
Persistent Identifierhttp://hdl.handle.net/10722/140806
ISSN
2015 Impact Factor: 4.218
2015 SCImago Journal Rankings: 2.552
ISI Accession Number ID
Funding AgencyGrant Number
National Science FoundationIIS 09-14631
National Natural Science Foundation of China60728204/F020404
Hong Kong Research Grants CouncilCUHK417107
Funding Information:

We would like to thank Chen Zhao for her advice on user study design and the anonymous reviewers for their valuable suggestions. Thanks also go to John Wright for video dubbing, Matt Callcut for proofreading, and all participants in our user study for making this paper possible. This work was partially supported by National Science Foundation (IIS 09-14631), National Natural Science Foundation of China (60728204/F020404), and Hong Kong Research Grants Council under General Research Funds (CUHK417107).

References

 

DC FieldValueLanguage
dc.contributor.authorWang, Ben_HK
dc.contributor.authorYu, Yen_HK
dc.contributor.authorWong, TTen_HK
dc.contributor.authorChen, Cen_HK
dc.contributor.authorXu, YQen_HK
dc.date.accessioned2011-09-23T06:19:32Z-
dc.date.available2011-09-23T06:19:32Z-
dc.date.issued2010en_HK
dc.identifier.citationACM Transactions On Graphics, 2010, v. 29 n. 6, article no. 146en_HK
dc.identifier.issn0730-0301en_HK
dc.identifier.urihttp://hdl.handle.net/10722/140806-
dc.descriptionProceedings of the 3rd ACM SIGGRAPH Asia 2010, Seoul, South Korea, 15-18 December 2010-
dc.description.abstractIt is often important for designers and photographers to convey or enhance desired color themes in their work. A color theme is typically defined as a template of colors and an associated verbal description. This paper presents a data-driven method for enhancing a desired color theme in an image. We formulate our goal as a unified optimization that simultaneously considers a desired color theme, texture-color relationships as well as automatic or user-specified color constraints. Quantifying the difference between an image and a color theme is made possible by color mood spaces and a generalization of an additivity relationship for two-color combinations. We incorporate prior knowledge, such as texture-color relationships, extracted from a database of photographs to maintain a natural look of the edited images. Experiments and a user study have confirmed the effectiveness of our method. © 2010 ACM.en_HK
dc.languageengen_US
dc.publisherAssociation for Computing Machinery, Inc.-
dc.relation.ispartofACM Transactions on Graphicsen_HK
dc.rightsACM Transactions on Graphics. Copyright © Association for Computing Machinery, Inc.-
dc.rights©ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions On Graphics, 2010, v. 29 n. 6, article no. 146. http://doi.acm.org/10.1145/1866158.1866172-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectcolor optimizationen_HK
dc.subjectcolor themeen_HK
dc.subjecthistogramsen_HK
dc.subjectsoft segmentationen_HK
dc.subjecttexture classesen_HK
dc.titleData-driven image color theme enhancementen_HK
dc.typeArticleen_HK
dc.identifier.emailYu, Y:yzyu@cs.hku.hken_HK
dc.identifier.authorityYu, Y=rp01415en_HK
dc.description.naturepostprint-
dc.identifier.doi10.1145/1866158.1866172en_HK
dc.identifier.scopuseid_2-s2.0-78650869613en_HK
dc.identifier.hkuros194309en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78650869613&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume29en_HK
dc.identifier.issue6en_HK
dc.identifier.spage146:1en_US
dc.identifier.epage146:10en_US
dc.identifier.isiWOS:000284943000010-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridWang, B=36816563200en_HK
dc.identifier.scopusauthoridYu, Y=8554163500en_HK
dc.identifier.scopusauthoridWong, TT=34974889700en_HK
dc.identifier.scopusauthoridChen, C=35274602700en_HK
dc.identifier.scopusauthoridXu, YQ=24462732200en_HK

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