Computational Color Constancy: Survey and Experiments
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 propose...
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| Veröffentlicht in: | IEEE transactions on image processing 2011-09, Vol.20 (9), p.2475-2489 |
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| container_end_page | 2489 |
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| container_issue | 9 |
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| container_title | IEEE transactions on image processing |
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| creator | Gijsenij, A. Gevers, T. van de Weijer, J. |
| description | 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 datasets. Finally, various freely available methods, of which some are considered to be state of the art, are evaluated on two datasets. |
| doi_str_mv | 10.1109/TIP.2011.2118224 |
| format | Article |
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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 datasets. Finally, various freely available methods, of which some are considered to be state of the art, are evaluated on two datasets.</description><subject>Adaptation model</subject><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Color</subject><subject>Color constancy</subject><subject>Computation</subject><subject>Computational modeling</subject><subject>Computer science; control theory; systems</subject><subject>Computer vision</subject><subject>Criteria</subject><subject>Estimation</subject><subject>Exact sciences and technology</subject><subject>Humans</subject><subject>illuminant estimation</subject><subject>Image color analysis</subject><subject>Image processing</subject><subject>Information, signal and communications theory</subject><subject>Light sources</subject><subject>Pattern recognition. Digital image processing. 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| ispartof | IEEE transactions on image processing, 2011-09, Vol.20 (9), p.2475-2489 |
| issn | 1057-7149 1941-0042 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Adaptation model Algorithms Applied sciences Artificial intelligence Color Color constancy Computation Computational modeling Computer science control theory systems Computer vision Criteria Estimation Exact sciences and technology Humans illuminant estimation Image color analysis Image processing Information, signal and communications theory Light sources Pattern recognition. Digital image processing. Computational geometry performance evaluation Pixel Signal processing State of the art survey Taxonomy Telecommunications and information theory |
| title | Computational Color Constancy: Survey and Experiments |
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