研究生: |
林聖耀 Lin, Sheng-Yao |
---|---|
論文名稱: |
Comparison on Numerical Methods for the Rudin-Osher-Fatemi Model Rudin-Osher-Fatemi 模型的數值方法比較 |
指導教授: |
王偉成
Wang, Wei-Cheng |
口試委員: |
黃聰明
Huang, Tsung-Ming 黃印良 Huang, Yin-Liang |
學位類別: |
碩士 Master |
系所名稱: |
理學院 - 數學系 Department of Mathematics |
論文出版年: | 2011 |
畢業學年度: | 99 |
語文別: | 英文 |
論文頁數: | 20 |
中文關鍵詞: | Rudin-Osher-Fatemi 模型的數值方法比較 |
外文關鍵詞: | Comparison on Numerical Methods for the Rudin-Osher-Fatemi Model |
相關次數: | 點閱:2 下載:0 |
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In this report, we introduce Rudin-Osher-Fatemi Model(ROF-Model) and some numerical methods for solving ROF-Model. And do some comparison on these methods for solving ROF-Model. Rudin-Osher-Fatemi Model is a famous and efficient model for image reconstruction. Because the nonlinear term in ROF-Model, to find an efficient and accurate method to solve ROF-Model is very important in image reconstruction.
Wotao Yin, Stanle, Donald Goldfarb, and Jerome Darbon, Bregman iterative algorithms for L_1-minimization with applications to compressed sensing, SIAM J. Imaging Sci., 1 (2008), pp. 143-168
A. Osher, Y. Mao, B. Dong, and W. Yin, An iterative regularization method for total variation-based image restoration, Multiscale Model. Simul., 4 (2005), pp. 460-489
T. Goldstein and S. Osher, The Split Bregman method for L1-regularized problems, SIAM J. Imaging Sci., 2 (2009), pp. 323-343
Chunlin Wu and Xue-Cheng Tai, Augmented Lagrangian Method, Dual Methods, and Split Bregman iteration for ROF, Vectorial TV, and High Order Models, SIAM J. Imaging Sci., pp. 300-339
Tony F. Chan, Gene H. Golub, and Pep Mulet, A Nonlinear Primal-Dual Method For Total Variation-Based Image Restoration, SIAM J. SCI. COMPUT Vol. 20, No. 6, pp. 1964-1977
Leonid I. Rudin, Stanley Osher and Emad Fatemi, Nonlinear total variation based removal algorithms, Physica D 60 (1992) 259-268
Yumei Huang, Michael K. NG, And You-Mei Wen, A Fast Total Variation Minimization Method for Image Restoration, Multiscale Model. Simul. Vol. 7, No. 2, pp. 774-795
Antonin Chambolle, An Algorithm for Total Variation Minimization and Applications, Journal of Mathematical Imaging and Vision 20: 89-97, 2004