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Mathematical Problems in Engineering
Volume 2014, Article ID 790547, 15 pages
http://dx.doi.org/10.1155/2014/790547
Research Article

TV+TV2 Regularization with Nonconvex Sparseness-Inducing Penalty for Image Restoration

Key Laboratory of Data Analysis and Image Processing, Chongqing University of Arts and Sciences, Chongqing, China

Received 24 September 2013; Revised 2 January 2014; Accepted 16 January 2014; Published 4 March 2014

Academic Editor: Suh-Yuh Yang

Copyright © 2014 Chengwu Lu and Hua Huang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [5 citations]

The following is the list of published articles that have cited the current article.

  • Guohao Lü, Siwei Luo, Yaping Huang, and Xinlan Jiang, “A novel regularization method based on convolution neural network,” Jisuanji Yanjiu yu Fazhan/Computer Research and Development, vol. 51, no. 9, pp. 1891–1900, 2014. View at Publisher · View at Google Scholar
  • Slavche Pejoski, Venceslav Kafedziski, and Dušan Gleich, “Compressed Sensing MRI Using Discrete Nonseparable Shearlet Transform and FISTA,” IEEE Signal Processing Letters, vol. 22, no. 10, pp. 1566–1570, 2015. View at Publisher · View at Google Scholar
  • Xiaoyan Liu, Xiangchu Feng, Xuande Zhang, Xiaoping Li, and Liang Luo, “Image Denoising via Asymptotic Nonlocal Filtering,” Mathematical Problems in Engineering, vol. 2015, pp. 1–9, 2015. View at Publisher · View at Google Scholar
  • Fan Liao, Jean Louis Coatrieux, Jiasong Wu, and Huazhong Shu, “A New Fast Algorithm for Constrained Four-Directional Total Variation Image Denoising Problem,” Mathematical Problems in Engineering, vol. 2015, pp. 1–11, 2015. View at Publisher · View at Google Scholar
  • J. Lei, W. Y. Liu, Q. B. Liu, X. Y. Wang, and S. Liu, “Shearlet regularization and dimensionality reduction for the temperature distribution sensing,” Measurement, vol. 82, pp. 176–187, 2016. View at Publisher · View at Google Scholar