Weighted Variational Minimization Model for Wavelet Domain Inpainting with Primal-Dual Method |
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Authors: | XU Jian-lou HAO Yan HAO Bin-bin ZHANG Feng-yun |
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Affiliation: | 1. School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471023, China 2. School of Science, China University of Petroleum, Qingdao 266580, China 3. School of Information Engineering, Shandong Youth University of Political Science, Jinan 250103, China |
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Abstract: | To preserve the edges and details of the image,a new variational model for wavelet domain inpainting was proposed which contained a non-convex regularizer. The non-convex regularizer can utilize the local information of image and perform better than those usual convex ones. In addition, to solve the non-convex minimization problem,an iterative reweighted method and a primaldual method were designed. The numerical experiments show that the new model not only gets better visual effects but also obtains higher signal to noise ratio than the recent method. |
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Keywords: | total variation wavelet inpainting primal-dual method |
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