Chinese Journal of Quantum Electronics, Volume. 32, Issue 3, 278(2015)
Image restoration based on nonlocal total variation
[4] [4] Paris Sylvain, Durand Fredo. A fast approximation of the bilateral filter using a signal processing approach [C]. European Conference on Computer Vision (ECCV), 2006, 568-580.
[6] [6] Rudin L I, Osher S, Fatimi E. Nonlinear total variation based noise removal algorithms [J]. Physica D, 1992, 60(1-4): 259-268.
[7] [7] Michailovich O V. An iterative shrinkage approach to total-variation image restoration [J]. IEEE Transactions on Image Processing, 2011, 20(5): 1281-1299.
[8] [8] Liu Gang, Huang Tingzhu, Liu Jun. High-order TVL1-based images restoration and spatially adapted regularization parameter selection [J]. Computers and Mathematics with Applications, 2014, 67(10): 2015-2026.
[9] [9] Buades A, Coll B, Morel J M. A nonlocal algorithm for image denoising [J]. Computer Vision and Pattern Recognition, 2005, 2: 60-65.
[10] [10] Dong Weisheng, Shi Guangming, Li Xin. Nonlocal image restoration with bilateral variance estimation: A low-rank approach [J]. IEEE Transactions on Image Processing, 2013, 22(2): 700-711.
[11] [11] Combettes P L, Wajs V R. Signal recovery by proximal forward-backward splitting [J]. Multiscale Modeling and Simulation, 2005, 4(4): 1168-1200.
[12] [12] Beck A, Teboulle M. Fast gradient-based algorithms for constrained total variation denoising and deblurring problems [J]. IEEE Transactions on Image Processing, 2009, 18(11): 2419-2434.
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ZHANG Jinhua, HOU Yan, YANG Jun. Image restoration based on nonlocal total variation[J]. Chinese Journal of Quantum Electronics, 2015, 32(3): 278
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Received: Oct. 27, 2014
Accepted: --
Published Online: May. 29, 2015
The Author Email: Jinhua ZHANG (jinhuazhang-zjh@163.com)