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This paper presents the study of the properties of graph colorings that minimize the quantity of color information with respect to a given probability distribution on the vertices. The minimum entropy of any coloring is the chromatic entropy. Applications of the chromatic entropy are found in coding with side information and digital image partition coding. We show that minimum entropy colorings are hard to compute even if a minimum cardinality coloring is given, the distribution is uniform, and the graph is planar. We also consider the minimum number of colors in a minimum entropy coloring, and show that this number can be arbitrarily larger than the chromatic number, even for restricted families of uniformly weighted graphs.