Adaptive variational models for image decomposition combining staircase reduction and texture extraction

作     者：Jiang Lingling Yin Haiqing Feng Xiangchu 

作者机构：School of Mathematics and Computational Science China Univ. of Petroleum Dongying 257061 P. R. China School of Science Xidian Univ. Xi'an 710071 P. R. China 

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

年 卷 期：2009年第20卷第2期

页      面：254-259页

核心收录：

学科分类：0839[工学-网络空间安全] 08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

主　　题：image decomposition total variation minimization bounded variation texture 

摘      要：New models for image decomposition are proposed which separate an image into a cartoon, consisting only of geometric objects, and an oscillatory component, consisting of textures or noise. The proposed models are given in a variational formulation with adaptive regularization norms for both the cartoon and texture parts. The adaptive behavior preserves key features such as object boundaries and textures while avoiding staircasing in what should be smooth regions. This decomposition is computed by minimizing a convex functional which depends on the two variables u and v, alternatively in each variable. Experimental results and comparisons to validate the proposed models are presented.