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

作　　者：Jiang Lingling Yin Haiqing Feng Xiangchu 

机构地区：[1]School of Mathematics and Computational Science, China Univ. of Petroleum, Dongying 257061, P. R. China [2]School of Science, Xidian Univ., Xi'an 710071, P. R. China

出　　处：《Journal of Systems Engineering and Electronics》2009年第2期254-259,共6页系统工程与电子技术（英文版）

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.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.

关 键 词：image decomposition total variation minimization bounded variation TEXTURE 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP393.08[自动化与计算机技术—计算机科学与技术]