标题：Iterative total variation image deblurring with varying regularized parameter
作者：Hao, Binbin ;Zhu, Jianguang ;Hao, Yan
作者机构：[Hao, Binbin ] College of Science, China University of Petroleum, Qingdao, China;[Hao, Yan ] School of Mahematics and Statistics, Henan University of 更多
会议名称：2014 6th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2014
会议日期：August 26, 2014 - August 27, 2014
来源：Proceedings - 2014 6th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2014
摘要：Total variation based model is one of the most effective method for image restoration. In this paper, we consider the total variation (TV) based regularization method and evaluate the regularization parameter for the TV based iterative forward-backward splitting (IFBS) approach. Different parameters with different iterations are obtained. The proposed adaptive iterative forward-backward splitting method does not need to know the initial value of the regularization parameter and does not require any information about the perturbation process. Experimental results demonstrate that the adaptive parameter method is efficient and provide competitive performance.
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