Weighted Variational Minimization Model for Wavelet Domain Inpainting with Primal-Dual Method

作     者：许建楼 郝岩 郝彬彬 张凤云 

作者机构：School of Mathematics and StatisticsHenan University of Science and Technology School of ScienceChina University of Petroleum Qingdao School of Information EngineeringShandong Youth University of Political Science 

出 版 物：《Journal of Donghua University(English Edition)》 (东华大学学报（英文版）)

年 卷 期：2014年第31卷第4期

页      面：458-462页

核心收录：

学科分类：1305[艺术学-设计学（可授艺术学、工学学位）] 13[艺术学] 081104[工学-模式识别与智能系统] 08[工学] 0804[工学-仪器科学与技术] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 

基　　金：National Natural Science Foundations of China(Nos.61301229,61101208) Doctoral Research Funds of Henan University of Science and Technology,China(Nos.09001708,09001751) 

主　　题：total variation wavelet inpainting primal-dual method 

摘      要：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.