Please use this identifier to cite or link to this item: https://doi.org/10.1137/070703533
Title: A fast total variation minimization method for image restoration
Authors: Huang, Y.
Ng, M.K.
Wen, Y.-W. 
Keywords: Deblurring
Denoising
Image restoration
Total variation
Issue Date: 2008
Citation: Huang, Y., Ng, M.K., Wen, Y.-W. (2008). A fast total variation minimization method for image restoration. Multiscale Modeling and Simulation 7 (2) : 774-795. ScholarBank@NUS Repository. https://doi.org/10.1137/070703533
Abstract: In this paper, we study a fast total variation minimization method for image restoration. In the proposed method, we use the modified total variation minimization scheme to denoise the deblurred image. An alternating minimization algorithm is employed to solve the proposed total variation minimization problem. Our experimental results show that the quality of restored images by the proposed method is competitive with those restored by the existing total variation restoration methods. We show the convergence of the alternating minimization algorithm and demonstrate that thealgorithm is very efficient. © 2008 Society for Industrial and applied Mathematics.
Source Title: Multiscale Modeling and Simulation
URI: http://scholarbank.nus.edu.sg/handle/10635/114978
ISSN: 15403459
DOI: 10.1137/070703533
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