Color transfer and its applications

Arvind Nayak, Subhasis Chaudhuri, Shilpa Inamdar

Research output: Contribution to journalArticle

Abstract

Varying illumination conditions result in images of a same scene differing widely in color and contrast. Accommodating such images is a problem ubiquitous in machine vision systems. A general approach is to map colors (or features extracted from colors within some pixel neighborhood) from a source image to those in some target image acquired under canonical conditions. This article reports two different methods, one neural network-based and the other multidimensional probability density function matching-based, developed to address the problem. We explain the problem, discuss the issues related to color correction and show the results of such an effort for specific applications. © 2008 Springer-Verlag Berlin Heidelberg.

Original languageEnglish
Pages (from-to)217-241
Number of pages25
JournalStudies in Computational Intelligence
Volume83
DOIs
Publication statusPublished - 2008

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Color
Probability density function
Computer vision
Lighting
Pixels
Neural networks

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Nayak, Arvind ; Chaudhuri, Subhasis ; Inamdar, Shilpa. / Color transfer and its applications. In: Studies in Computational Intelligence. 2008 ; Vol. 83. pp. 217-241.
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Color transfer and its applications. / Nayak, Arvind; Chaudhuri, Subhasis; Inamdar, Shilpa.

In: Studies in Computational Intelligence, Vol. 83, 2008, p. 217-241.

Research output: Contribution to journalArticle

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