When we use usual color spaces for image processing, there are some problems in the conventional image coding. In a usual color space each coordinate has correlation with another, and may represent unnecessary points because the shape of Gamut is complex. To solve the problems we propose Optimum Color Space Transform using principal component analysis. When the CIE_L*a*b* uniform color coordinates is transformed to the optimum color space, three new components have no correlation with one another. The optimum color space is efficient for image coding in terms of redundant reduction. Further more, this transform can be applied to color image analysis such as region segmentation, color restriction scheme. As a result, the optimum color space transform has a good performance for image coding and feature analysis.
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