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A Spectral Color Analysis and Colorization Technique
September/October 2006 (vol. 26 no. 5)
pp. 74-82
Vladimir Bochko, Lappeenranta University of Technology
Jussi Parkkinen, University of Joensuu
As the demand for colorization increases, so does the need for an automated technique. 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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Index Terms:
color, computer vision, machine learning
Citation:
Vladimir Bochko, Jussi Parkkinen, "A Spectral Color Analysis and Colorization Technique," IEEE Computer Graphics and Applications, vol. 26, no. 5, pp. 74-82, Sept.-Oct. 2006, doi:10.1109/MCG.2006.95
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