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Single-image super-resolution using directional total variation regularization and alternating direction method of multiplier solver

[+] Author Affiliations
Qiang Wang, Zhenghua Wu, Mingjian Sun, Ting Liu, Bo Li, Naizhang Feng, Yi Shen

Harbin Institute of Technology, Department of Control Science and Engineering, Room 602, Main building 92 West Dazhi Street, Nangang District, Harbin 150001, China

J. Electron. Imaging. 24(2), 023026 (Apr 07, 2015). doi:10.1117/1.JEI.24.2.023026
History: Received November 1, 2014; Accepted March 17, 2015
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Abstract.  Single-image super-resolution (SR) is one of the most important and challenging issues in image processing. To produce a high-resolution image from a low-resolution image, one of the conventional approaches is to leverage regularization to overcome the limitations caused by the modeling. However, conventional regularizers such as total variation always neglect the high-level structures in the data. To overcome the drawback, we propose to explore the underlying information for the images with structured edges by using directional total variation. An alternating direction method of a multiplier-based algorithm is presented to effectively solve the resulting optimization problem. Computer simulations on several texture images such as a leaf image have been used to demonstrate the effectiveness and improvement of the proposed method on SR reconstruction, both qualitatively and quantitatively. Furthermore, the effect of parameter selection is also discussed for the proposed method.

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Citation

Qiang Wang ; Zhenghua Wu ; Mingjian Sun ; Ting Liu ; Bo Li, et al.
"Single-image super-resolution using directional total variation regularization and alternating direction method of multiplier solver", J. Electron. Imaging. 24(2), 023026 (Apr 07, 2015). ; http://dx.doi.org/10.1117/1.JEI.24.2.023026


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