Image decomposition and staircase effect reduction based on total generalized variation

作     者：Jianlou Xu Xiangchu Feng Yan Hao Yu Han 

作者机构：School of ScienceXidian University School of Mathematics and StatisticsHenan University of Science and Technology College of Mathematic and Computational ScienceShenzhen University 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2014年第25卷第1期

页      面：168-174页

核心收录：

学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 0814[工学-土木工程] 082301[工学-道路与铁道工程] 0823[工学-交通运输工程] 

基　　金：supported by the National Natural Science Foundation of China(61271294 61301229) the Doctoral Research Fund of Henan University of Science and Technology(09001708 09001751) 

主　　题：total variation (TV) image decomposition staircaseeffect total generalized variation. 

摘      要：Total variation （TV） is widely applied in image process-ing. The assumption of TV is that an image consists of piecewise constants, however, it suffers from the so-cal ed staircase effect. In order to reduce the staircase effect and preserve the edges when textures of image are extracted, a new image decomposition model is proposed in this paper. The proposed model is based on the to-tal generalized variation method which involves and balances the higher order of the structure. We also derive a numerical algorithm based on a primal-dual formulation that can be effectively imple-mented. Numerical experiments show that the proposed method can achieve a better trade-off between noise removal and texture extraction, while avoiding the staircase effect efficiently.