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Volume 1, Issue 3
Fast Algorithms for the Anisotropic LLT Model in Image Denoising

Zhi-Feng Pang, Li-Lian Wang & Yu-Fei Yang

East Asian J. Appl. Math., 1 (2011), pp. 264-283.

Published online: 2018-02

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  • Abstract

In this paper, we propose a new projection method for solving a general minimization problems with two $L^1$-regularization terms for image denoising. It is related to the split Bregman method, but it avoids solving PDEs in the iteration. We employ the fast iterative shrinkage-thresholding algorithm (FISTA) to speed up the proposed method to a convergence rate $O$($k^-$$^2$). We also show the convergence of the algorithms. Finally, we apply the methods to the anisotropic Lysaker, Lundervold and Tai (LLT) model and demonstrate their efficiency.

  • AMS Subject Headings

65M10, 78A48

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COPYRIGHT: © Global Science Press

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@Article{EAJAM-1-264, author = {Zhi-Feng Pang, Li-Lian Wang and Yu-Fei Yang}, title = {Fast Algorithms for the Anisotropic LLT Model in Image Denoising}, journal = {East Asian Journal on Applied Mathematics}, year = {2018}, volume = {1}, number = {3}, pages = {264--283}, abstract = {

In this paper, we propose a new projection method for solving a general minimization problems with two $L^1$-regularization terms for image denoising. It is related to the split Bregman method, but it avoids solving PDEs in the iteration. We employ the fast iterative shrinkage-thresholding algorithm (FISTA) to speed up the proposed method to a convergence rate $O$($k^-$$^2$). We also show the convergence of the algorithms. Finally, we apply the methods to the anisotropic Lysaker, Lundervold and Tai (LLT) model and demonstrate their efficiency.

}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.231210.260411a}, url = {http://global-sci.org/intro/article_detail/eajam/10908.html} }
TY - JOUR T1 - Fast Algorithms for the Anisotropic LLT Model in Image Denoising AU - Zhi-Feng Pang, Li-Lian Wang & Yu-Fei Yang JO - East Asian Journal on Applied Mathematics VL - 3 SP - 264 EP - 283 PY - 2018 DA - 2018/02 SN - 1 DO - http://doi.org/10.4208/eajam.231210.260411a UR - https://global-sci.org/intro/article_detail/eajam/10908.html KW - Image denoising, anisotropic LLT model, Douglas-Rachford splitting method, split Bregman method, projection method, fast projection method. AB -

In this paper, we propose a new projection method for solving a general minimization problems with two $L^1$-regularization terms for image denoising. It is related to the split Bregman method, but it avoids solving PDEs in the iteration. We employ the fast iterative shrinkage-thresholding algorithm (FISTA) to speed up the proposed method to a convergence rate $O$($k^-$$^2$). We also show the convergence of the algorithms. Finally, we apply the methods to the anisotropic Lysaker, Lundervold and Tai (LLT) model and demonstrate their efficiency.

Zhi-Feng Pang, Li-Lian Wang and Yu-Fei Yang. (2018). Fast Algorithms for the Anisotropic LLT Model in Image Denoising. East Asian Journal on Applied Mathematics. 1 (3). 264-283. doi:10.4208/eajam.231210.260411a
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