A fast algorithm for the total variation model of image denoising

Advances in Computational Mathematics

Volumn 33, Issue 2, 2010, Pages 231-241

  Jia, Rong Qing ^a   Zhao, Hanqing ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

Image denoising; Optimization; Total variation

Indexed keywords

EID: 77954087952     PISSN: 10197168     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10444-009-9128-5     Document Type: Article

References (5)

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3. Jia, R. Q., Zhao, H. Q., Zhao, W.: Convergence analysis of the Bregman method for the variational model of image denoising. Appl. Comput. Harmon. Anal. (2009). doi: 10. 1016/j. acha. 2009. 05. 002.
4. Osher, S., Burger, M., Goldfarb, D., Xu, J. J., Yin, W. T.: An iterative regularization method for total variation-based image restoration. Multiscale Model. Simul. 4, 460-489 (2005).
5. Rudin, L., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Phys. D 60, 259-268 (1992).