A primal dual proximal point method of Chambolle-Pock algorithms for ℓ1-TV minimization problems in image reconstruction

Author

Yuchao Tang ; Jigen Peng ; Shigang Yue ; Jiawei Xu

Author_Institution

Dept. of Math., Nanchang Univ., Nanchang, China

fYear

2012

fDate

16-18 Oct. 2012

Firstpage

12

Lastpage

16

Abstract

Computed tomography (CT) image reconstruction problems can be solved by finding the minimizer of a suitable objective function. The objective function usually consists of a data fidelity term and a regularization term. Total variation (TV) minimization problems are widely used for solving incomplete data problems in CT image reconstruction. In this paper, we focus on the CT image reconstruction model which combines the TV regularization and ℓ₁ data error term. We introduce a primal dual proximal point method of Chambolle-Pock algorithm to solve the proposed optimization problem. We tested it on computer simulated data and the experiment results shown it exhibited good performance when used to few-view CT image reconstruction.

Keywords

computerised tomography; image reconstruction; medical image processing; minimisation; ℓ₁ data error term; ℓ₁-TV minimization problem; Chambolle-Pock algorithm; computed tomography; data fidelity term; data regularization term; few-view CT image reconstruction; objective function; optimization problem; primal dual proximal point method; total variation minimization problem; total variation regularization;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on

Conference_Location

Chongqing

Print_ISBN

978-1-4673-1183-0

Type

conf

DOI

10.1109/BMEI.2012.6513092

Filename

6513092