Title :
Image Decomposition Using Bregman-GTV and Meyer´s G-Norm
Author :
Lu Chengwu ; Zhou Daoqing
Author_Institution :
Key Lab. of Data Anal. & Image Process., Chongqing Univ. of Arts & Sci. Chongqing, Chongqing, China
Abstract :
In order to avoid stair casing and preserve small scale texture information for the classical total variation regularization, a new minimization energy functional model for image decomposition is proposed. We firstly introduce a generalized total variational regularization. The oscillatory component containing texture and/or noise is modeled in generalized function space. And then, the proposed model is numerically implemented by using a preconditioned Split Bregman method. Experiments show that the proposed model can avoid efficiently the staircasing effect, at the same time, both well remain edge and texture.
Keywords :
image texture; minimisation; Bregman-GTV; Meyer G-Norm; classical total variation regularization; generalized function space; generalized total variational regularization; image decomposition; minimization energy functional model; preconditioned Split Bregman method; small scale texture information preservation; stair casing avoidance; Computational modeling; Image decomposition; Image edge detection; Mathematical model; Numerical models; TV; G-norm; generalized total variation; image decomposition; regularization;
Conference_Titel :
Intelligent Networking and Collaborative Systems (INCoS), 2013 5th International Conference on
Conference_Location :
Xi´an
DOI :
10.1109/INCoS.2013.142