Issue No.05 - September/October (2006 vol.26)
Vladimir Bochko , Lappeenranta University of Technology
Jussi Parkkinen , University of Joensuu
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2006.95
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
Vladimir Bochko, Jussi Parkkinen, "A Spectral Color Analysis and Colorization Technique", IEEE Computer Graphics and Applications, vol.26, no. 5, pp. 74-82, September/October 2006, doi:10.1109/MCG.2006.95