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Single-image super-resolution based on Markov random field and contourlet transform

[+] Author Affiliations
Wei Wu

Sichuan University, School of Electronics and Information Engineering, Chengdu, 610064 China

Zheng Liu

University of Ottawa, School of Information Technology and Engineering, Ottawa, Ontario, K1A 0R6 Canada

Wail Gueaieb

University of Ottawa, School of Information Technology and Engineering, Ottawa, Ontario, K1A 0R6 Canada

Xiaohai He

Sichuan University, School of Electronics and Information Engineering, Chengdu, 610064 China

J. Electron. Imaging. 20(2), 023005 (April 22, 2011). doi:10.1117/1.3580750
History: Received May 25, 2010; Revised March 14, 2011; Accepted March 31, 2011; Published April 22, 2011; Online April 22, 2011
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Learning-based methods are well adopted in image super-resolution. In this paper, we propose a new learning-based approach using contourlet transform and Markov random field. The proposed algorithm employs contourlet transform rather than the conventional wavelet to represent image features and takes into account the correlation between adjacent pixels or image patches through the Markov random field (MRF) model. The input low-resolution (LR) image is decomposed with the contourlet transform and fed to the MRF model together with the contourlet transform coefficients from the low- and high-resolution image pairs in the training set. The unknown high-frequency components/coefficients for the input low-resolution image are inferred by a belief propagation algorithm. Finally, the inverse contourlet transform converts the LR input and the inferred high-frequency coefficients into the super-resolved image. The effectiveness of the proposed method is demonstrated with the experiments on facial, vehicle plate, and real scene images. A better visual quality is achieved in terms of peak signal to noise ratio and the image structural similarity measurement.

© 2011 SPIE and IS&T

Citation

Wei Wu ; Zheng Liu ; Wail Gueaieb and Xiaohai He
"Single-image super-resolution based on Markov random field and contourlet transform", J. Electron. Imaging. 20(2), 023005 (April 22, 2011). ; http://dx.doi.org/10.1117/1.3580750


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