Abstract
Colorization is a computerized process in which color is added to a gray-level image or movie. As the demand for colorization increases, so does the need for an automated technique. We analyze color in the spectral domain and present a spectral color-picking and colorization technique for surface color coating. A solution to the color-picking task involves principal component analysis-based learning techniques such as a mixture model of probabilistic principal component analyzers and regressive PCA. Experimental results confirm the method's feasibility
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