A comparison of computational color constancy algorithms. I: Methodology and experiments with synthesized data

By Kobus Barnard, Vlad C. Cardei, Brian V. Funt. IEEE Transactions on Image Processing, 2002

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Edge-Based Color Constancy (2007, unknown): “Although these simple color constancy algorithms are slightly outperformed by more elaborate methods, e.g. gamut mapping, they perform surprisingly well while they are conceptually simpler (for an extensive evaluation of multiple color constancy methods see [3], [15], [16]).”
A comparison of computational color constancy Algorithms. II. Experiments with image data (2002, methodology): “We report results for a sigma of 8 (see part one [3] for further discussion).”
Computational Color Constancy: Survey and Experiments (2011, unknown): “Ideally, both types of data should be used for a thorough evaluation of color constancy methods [52], [81].”
Color constancy. (2011, unknown): “In the machine-vision literature, it is more common to record an unscaled measure of the difference between ideal and empirical matches or one converted to an angular measure with respect to the origin of the color space of interest (Barnard et al., 2002; Hordley & Finlayson, 2006). Perceptually wei”