title: Iterative nonlocal total variation regularization method for image restoration.
abstract: In this paper, a Bregman iteration based total variation image restoration algorithm is proposed. Based on the Bregman iteration, the algorithm splits the original total variation problem into sub-problems that are easy to solve. Moreover, non-local regularization is introduced into the proposed algorithm, and a method to choose the non-local filter parameter locally and adaptively is proposed. Experiment results show that the proposed algorithms outperform some other regularization methods.
authors.affiliation: School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu, China.
authors.forename: Huanyu
authors.initials: H
authors.lastname: Xu
authors.forename: Quansen
authors.initials: Q
authors.lastname: Sun
authors.forename: Nan
authors.initials: N
authors.lastname: Luo
authors.forename: Guo
authors.initials: G
authors.lastname: Cao
authors.forename: Deshen
authors.initials: D
authors.lastname: Xia
mesh_terms: D000465:Algorithms; D007089:Image Enhancement; D007090:Image Interpretation, Computer-Assisted