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Article: A contrast maximization method for color-to-grayscale conversion

TitleA contrast maximization method for color-to-grayscale conversion
Authors
KeywordsConvex optimization
Regularization
Color-to-grayscale
Issue Date2015
Citation
Multidimensional Systems and Signal Processing, 2015, v. 26, n. 3, p. 869-877 How to Cite?
Abstract© 2014, Springer Science+Business Media New York. In this paper, we study how to convert a color image to a grayscale image, and consider an effective contrast maximization method for color-to-grayscale conversion. Our method is based on the combination of red, green and blue channels pixel values. The optimization problem involves the maximization of the variance of the output grayscale image, the data-fitting term between the brightness of the input and output images. A regularization term is also added to make the resulting objective function to be convex and obtain a stable combination of red, green and blue pixel values. Experimental results on a set of benchmark color images are reported to demonstrate the effectiveness of the proposed method, and that its performance is better than those obtained by the other testing methods.
Persistent Identifierhttp://hdl.handle.net/10722/276548
ISSN
2023 Impact Factor: 1.7
2023 SCImago Journal Rankings: 0.499
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorJin, Zhengmeng-
dc.contributor.authorNg, Michael K.-
dc.date.accessioned2019-09-18T08:33:56Z-
dc.date.available2019-09-18T08:33:56Z-
dc.date.issued2015-
dc.identifier.citationMultidimensional Systems and Signal Processing, 2015, v. 26, n. 3, p. 869-877-
dc.identifier.issn0923-6082-
dc.identifier.urihttp://hdl.handle.net/10722/276548-
dc.description.abstract© 2014, Springer Science+Business Media New York. In this paper, we study how to convert a color image to a grayscale image, and consider an effective contrast maximization method for color-to-grayscale conversion. Our method is based on the combination of red, green and blue channels pixel values. The optimization problem involves the maximization of the variance of the output grayscale image, the data-fitting term between the brightness of the input and output images. A regularization term is also added to make the resulting objective function to be convex and obtain a stable combination of red, green and blue pixel values. Experimental results on a set of benchmark color images are reported to demonstrate the effectiveness of the proposed method, and that its performance is better than those obtained by the other testing methods.-
dc.languageeng-
dc.relation.ispartofMultidimensional Systems and Signal Processing-
dc.subjectConvex optimization-
dc.subjectRegularization-
dc.subjectColor-to-grayscale-
dc.titleA contrast maximization method for color-to-grayscale conversion-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s11045-014-0295-2-
dc.identifier.scopuseid_2-s2.0-85027947066-
dc.identifier.volume26-
dc.identifier.issue3-
dc.identifier.spage869-
dc.identifier.epage877-
dc.identifier.eissn1573-0824-
dc.identifier.isiWOS:000357298100017-
dc.identifier.issnl0923-6082-

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