Color Constancy Using Natural Image Statistics and Scene Semantics

8 years 2 months ago
Color Constancy Using Natural Image Statistics and Scene Semantics
—Existing color constancy methods are all based on specific assumptions such as the spatial and spectral characteristics of images. As a consequence, no algorithm can be considered as universal. However, with the large variety of available methods, the question is how to select the method that performs best for a specific image. To achieve selection and combining of color constancy algorithms, in this paper, natural image statistics are used to identify the most important characteristics of color images. Then, based on these image characteristics, the proper color constancy algorithm (or best combination of algorithms) is selected for a specific image. To capture the image characteristics, the Weibull parameterization (e.g. grain size and contrast) is used. It is shown that the Weibull parameterization is related to the image attributes to which the used color constancy methods are sensitive to. A MoG-classifier is used to learn the correlation and weighting between the Weibull-p...
Arjan Gijsenij, Theo Gevers
Added 14 May 2011
Updated 14 May 2011
Type Journal
Year 2011
Where PAMI
Authors Arjan Gijsenij, Theo Gevers
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