A novel method of image colorization is proposed. It overcomes the problem existed in algorithm of image colorization based on dictionary learning and sparse representation. First,multiple blocks from reference color images was selected according to the sub-contents of target gray-scale image.Second,the multiple blocks are trained respectively to obtain classified dictionaries based on contents.Finally,the best matching sub-dictionary can be decided by minimizing the reconstruction error and the gray-scale ...
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