A colorization algorithm based on local MAP estimation

This paper presents a colorization algorithm which adds color to monochrome images. In this paper, the colorization problem is formulated as the maximum a posteriori (MAP) estimation of a color image given a monochrome image. Markov random field (MRF) is used for modeling a color image which is util...

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Bibliographic Details
Published inPattern recognition Vol. 39; no. 11; pp. 2212 - 2217
Main Authors Noda, Hideki, Korekuni, Jin, Niimi, Michiharu
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.11.2006
Subjects
Colorization
MAP estimation
Monochrome image
MRF
MAP estimation
MRF
Colorization
Monochrome image
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Summary:This paper presents a colorization algorithm which adds color to monochrome images. In this paper, the colorization problem is formulated as the maximum a posteriori (MAP) estimation of a color image given a monochrome image. Markov random field (MRF) is used for modeling a color image which is utilized as a prior for the MAP estimation. The MAP estimation problem for a whole image is decomposed into local MAP estimation problems for each pixel. Using 0.6% of whole pixels as references, the proposed method produced pretty high quality color images with 25.7–32.6 dB PSNR values for eight images.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2006.03.015