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Author Arjan Gijsenij; Theo Gevers; Joost Van de Weijer
Title (down) Physics-based Edge Evaluation for Improved Color Constancy Type Conference Article
Year 2009 Publication 22nd IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages 581 – 588
Keywords
Abstract Edge-based color constancy makes use of image derivatives to estimate the illuminant. However, different edge types exist in real-world images such as shadow, geometry, material and highlight edges. These different edge types may have a distinctive influence on the performance of the illuminant estimation.
Address Miami, USA
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1063-6919 ISBN 978-1-4244-3992-8 Medium
Area Expedition Conference CVPR
Notes CAT;ISE Approved no
Call Number CAT @ cat @ GGW2009 Serial 1197
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Author Arjan Gijsenij; Theo Gevers; Joost Van de Weijer
Title (down) Generalized Gamut Mapping using Image Derivative Structures for Color Constancy Type Journal Article
Year 2010 Publication International Journal of Computer Vision Abbreviated Journal IJCV
Volume 86 Issue 2-3 Pages 127-139
Keywords
Abstract The gamut mapping algorithm is one of the most promising methods to achieve computational color constancy. However, so far, gamut mapping algorithms are restricted to the use of pixel values to estimate the illuminant. Therefore, in this paper, gamut mapping is extended to incorporate the statistical nature of images. It is analytically shown that the proposed gamut mapping framework is able to include any linear filter output. The main focus is on the local n-jet describing the derivative structure of an image. It is shown that derivatives have the advantage over pixel values to be invariant to disturbing effects (i.e. deviations of the diagonal model) such as saturated colors and diffuse light. Further, as the n-jet based gamut mapping has the ability to use more information than pixel values alone, the combination of these algorithms are more stable than the regular gamut mapping algorithm. Different methods of combining are proposed. Based on theoretical and experimental results conducted on large scale data sets of hyperspectral, laboratory and realworld scenes, it can be derived that (1) in case of deviations of the diagonal model, the derivative-based approach outperforms the pixel-based gamut mapping, (2) state-of-the-art algorithms are outperformed by the n-jet based gamut mapping, (3) the combination of the different n-jet based gamut
Address
Corporate Author Thesis
Publisher Kluwer Academic Publishers Hingham, MA, USA Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0920-5691 ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number CAT @ cat @ GGW2010 Serial 1274
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Author Arjan Gijsenij; Theo Gevers; Joost Van de Weijer
Title (down) Edge Classification for Color Constancy Type Conference Article
Year 2008 Publication 4th European Conference on Colour in Graphics, Imaging and Vision Proceedings Abbreviated Journal
Volume Issue Pages 231–234
Keywords
Abstract
Address Terrassa (Spain)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CGIV08
Notes CAT;ISE Approved no
Call Number CAT @ cat @ GGV2008a Serial 967
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Author Arjan Gijsenij; Theo Gevers; Joost Van de Weijer
Title (down) Computational Color Constancy: Survey and Experiments Type Journal Article
Year 2011 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 20 Issue 9 Pages 2475-2489
Keywords computational color constancy;computer vision application;gamut-based method;learning-based method;static method;colour vision;computer vision;image colour analysis;learning (artificial intelligence);lighting
Abstract Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-the- art methods. Several criteria are proposed that are used to assess the approaches. A taxonomy of existing algorithms is proposed and methods are separated in three groups: static methods, gamut-based methods and learning-based methods. Further, the experimental setup is discussed including an overview of publicly available data sets. Finally, various freely available methods, of which some are considered to be state-of-the-art, are evaluated on two data sets.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1057-7149 ISBN Medium
Area Expedition Conference
Notes ISE;CIC Approved no
Call Number Admin @ si @ GGW2011 Serial 1717
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