An linearized alternating direction method for total variation image restoration

Author

Xiao Jing Jing ; Yang Min

Author_Institution

Coll. of Autom., Nanjing Univ. of Posts & Telecommun., Nanjing, China

fYear

2015

fDate

23-25 May 2015

Firstpage

5626

Lastpage

5629

Abstract

Total variation (TV) regularization is popular in image reconstruction due to its edge-preserving property. In this paper, we propose to solve the TV regularized problem by linearized alternating minimization method based on the augmented Lagrangian function at each iteration and a Barzilai-Borwein (BB) stepsize rule. Numerical results show that the linearized alternating direction method can restore the degraded image with high quality, good convergence and stability.

Keywords

image restoration; iterative methods; BB stepsize rule; Barzilai-Borwein stepsize rule; TV regularization; augmented Lagrangian function; degraded image; edge-preserving property; image reconstruction; iteration; linearized alternating direction method; linearized alternating minimization method; total variation image restoration; Gold; Image reconstruction; Image restoration; Imaging; Linear programming; Minimization; TV; Barzilai-Borwein (BB) stepsize; Image reconstruction; Linearized alternating direction method; Total variation;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2015 27th Chinese

Conference_Location

Qingdao

Print_ISBN

978-1-4799-7016-2

Type

conf

DOI

10.1109/CCDC.2015.7161803

Filename

7161803