Image colorization via color propagation and rank minimization

Image colorization aims to add colors to grayscale images, which used to be a time-consuming and tedious task that requires lots of human efforts. In this paper, we present a novel colorization method based on color propagation and rank minimization. Given a small portion of chrominance values and a...

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Bibliographic Details
Published in2015 IEEE International Conference on Image Processing (ICIP) pp. 4228 - 4232
Main Authors Yonggen Ling, Au, Oscar C., Jiahao Pang, Jin Zeng, Yuan Yuan, Amin Zheng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2015
Subjects
Color
Colored noise
Colorization
Gray-scale
Image color analysis
image restoration
matrix completion
Minimization
rank minimization
Redundancy
Yttrium
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Summary:Image colorization aims to add colors to grayscale images, which used to be a time-consuming and tedious task that requires lots of human efforts. In this paper, we present a novel colorization method based on color propagation and rank minimization. Given a small portion of chrominance values and a grayscale image, we firstly propagate the known color values to other pixels to be colorized. As the colorized image after color propagation is not accurate, we then define a confidence matrix to measure the propagation fidelity. Finally, pixels that have propagated chrominance values with confidence are colorized by rank minimization, which exploits the redundancy of natural images. Experimental results on real data set show that our proposed method achieves state-of-the-art colorization quality.
DOI:10.1109/ICIP.2015.7351603