http://dx.doi.org/10.1137/130915406">
 

Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

Total variation structured total least squares method for image restoration

Language

English

Abstract

In this paper, we study the total variation structured total least squares method for image restoration. In the image restoration problem, the point spread function is corrupted by errors. In the model, we study the objective function by minimizing two variables: the restored image and the estimated error of the point spread function. The proposed objective function consists of the data-fitting term containing these two variables, the magnitude of error and the total variation regularization of the restored image. By making use of the structure of the objective function, an efficient alternating minimization scheme is developed to solve the proposed model. Numerical examples are also presented to demonstrate the effectiveness of the proposed model and the efficiency of the numerical scheme.Copyright © by SIAM.

Keywords

Alternating minimization, Image restoration, Regularization, Structured total least squares, Total variation

Publication Date

2013

Source Publication Title

SIAM Journal on Scientific Computing

Volume

35

Issue

6

Start Page

B1304

End Page

B1320

Publisher

Society for Industrial and Applied Mathematics

ISSN (print)

10648275

ISSN (electronic)

10957197

This document is currently not available here.

Share

COinS