Gamut Constrained Illuminant Estimation
International Journal of Computer Vision
Dichromatic illumination estimation without pre-segmentation
Pattern Recognition Letters
Classification-Based Color Constancy
VISUAL '08 Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management
Region-Based Illuminant Estimation for Effective Color Correction
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Automatic color constancy algorithm selection and combination
Pattern Recognition
Color constancy using denoising methods and cepstral analysis
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Perceptually motivated automatic color contrast enhancement based on color constancy estimation
Journal on Image and Video Processing - Special issue on emerging methods for color image and video quality enhancement
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We present a re-evaluation of previous experimental data for five different colour constancy algorithms, based on experiments on real and synthetic images. Our work is motivated by the observation that previous analysis of algorithm performance is flawed because it uses inappropriate statistical measures of performance. We discuss these flaws in detail and suggest more appropriate statistical tests. We show that using these tests conclusions as to the relative performance of algorithms are significantly changed as compared to the original analysis of the data. In particular we conclude that the performance of two algorithms: Gamut Mapping and Color by Correlation is statistically equivalent and significantly better than the three other algorithms tested (Max-RGB and two versions of Grey-world).