Issue No. 05 - September/October (2006 vol. 26)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2006.95
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.
color, computer vision, machine learning
V. Bochko and J. Parkkinen, "A Spectral Color Analysis and Colorization Technique," in IEEE Computer Graphics and Applications, vol. 26, no. , pp. 74-82, 2006.