A Fourth Order Dual Method for Iteration Regularization with H-1 Fidelity Based Denoising

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Volume 2, Issue 3

J. Info. Comput. Sci. , 2 (2007), pp. 172-178.

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Abstract

In this paper, we propose iterative regularization for image denoising problems, based on the total variation minimizing models proposed by Rudin, Osher, and Fatemi(ROF). Besides, considering the staircase occuring in the process of denoising, we combine the higher order derivatives, and use iterative scheme. The fourth order dual method is used to solve the minimization problems. The numerical experiments show the iterative procedure preserves more details and reduces staircasing. Besides, it can be claimed that the fourth order dual method is more faster and stable than time marching algorithms.

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image denoising total variation fourth order dual method iterative regularization

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@Article{JICS-2-172, author = {}, title = {A Fourth Order Dual Method for Iteration Regularization with H-1 Fidelity Based Denoising}, journal = {Journal of Information and Computing Science}, year = {2007}, volume = {2}, number = {3}, pages = {172--178}, abstract = {In this paper, we propose iterative regularization for image denoising problems, based on the total variation minimizing models proposed by Rudin, Osher, and Fatemi(ROF). Besides, considering the staircase occuring in the process of denoising, we combine the higher order derivatives, and use iterative scheme. The fourth order dual method is used to solve the minimization problems. The numerical experiments show the iterative procedure preserves more details and reduces staircasing. Besides, it can be claimed that the fourth order dual method is more faster and stable than time marching algorithms. }, issn = {3080-180X}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22795.html} }

TY - JOUR T1 - A Fourth Order Dual Method for Iteration Regularization with H-1 Fidelity Based Denoising AU - JO - Journal of Information and Computing Science VL - 3 SP - 172 EP - 178 PY - 2007 DA - 2007/09 SN - 2 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22795.html KW - image denoising KW - total variation KW - fourth order dual method KW - iterative regularization AB - In this paper, we propose iterative regularization for image denoising problems, based on the total variation minimizing models proposed by Rudin, Osher, and Fatemi(ROF). Besides, considering the staircase occuring in the process of denoising, we combine the higher order derivatives, and use iterative scheme. The fourth order dual method is used to solve the minimization problems. The numerical experiments show the iterative procedure preserves more details and reduces staircasing. Besides, it can be claimed that the fourth order dual method is more faster and stable than time marching algorithms.

. (2007). A Fourth Order Dual Method for Iteration Regularization with H-1 Fidelity Based Denoising. Journal of Information and Computing Science. 2 (3). 172-178. doi:

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