A Spectral Color Analysis and Colorization Technique

Author

Bochko, Vladimir ; Parkkinen, Jussi

Author_Institution

Lappeenranta Univ. of Technol.

Volume

26

Issue

5

fYear

2006

Firstpage

74

Lastpage

82

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

Keywords

image colour analysis; image resolution; learning (artificial intelligence); principal component analysis; probability; regression analysis; automated colorization technique; computerized colorization technique; gray-level image; gray-level movie; principal component analysis-based learning technique; probabilistic principal component analyzer; regressive PCA; spectral color-picking; spectral image color analysis; surface color coating; Computer graphics; Covariance matrix; Data structures; Equations; Image color analysis; Multidimensional systems; Pixel; Principal component analysis; Spectral analysis; Vectors; color; computer vision; machine learning;

fLanguage

English

Journal_Title

Computer Graphics and Applications, IEEE

Publisher

ieee

ISSN

0272-1716

Type

jour

DOI

10.1109/MCG.2006.95

Filename

1683696