A Spectral Color Analysis and Colorization Technique
IEEE Computer Graphics and Applications
Color Constancy Based on Image Similarity
IEICE - Transactions on Information and Systems
Automatic color constancy algorithm selection and combination
Pattern Recognition
Generalized Gamut Mapping using Image Derivative Structures for Color Constancy
International Journal of Computer Vision
Color constancy using denoising methods and cepstral analysis
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A Solution of the Dichromatic Model for Multispectral Photometric Invariance
International Journal of Computer Vision
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Computational colour constancy tries to recover the colour of the scene illuminant of an image. Colour constancy algorithms can, in general, be divided into two groups: statistics-based approaches that exploit statistical knowledge of common lights and surfaces, and physics-based algorithms which are based on an understanding of how physical processes such as highlights manifest themselves in images. A combined physical and statistical colour constancy algorithm that integrates the advantages of the statistics-based Colour by Correlation method with those of a physics-based technique based on the dichromaticreflectance model is introduced. In contrast to other approaches not only a single illuminant estimate is provided but a set of likelihoods for a given illumination set. Experimental results on the benchmark Simon Fraser image database show the combined method to clearly out-perform purely statistical and purely physical algorithms.