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Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

On algorithms for automatic deblurring from a single image

Language

English

Abstract

In this paper, we study two variational blind deblurring models for a single image. The first model is to use the total variation prior in both image and blur, while the second model is to use the frame based prior in both image and blur. The main contribution of this paper is to show how to employ the generalized cross validation (GCV) method efficiently and automatically to estimate the two regularization parameters associated with the priors in these two blind motion deblurring models. Our experimental results show that the visual quality of restored images by the proposed method is very good, and they are competitive with the tested existing methods. We will also demonstrate the proposed method is also very efficient. Copyright 2012 by AMSS, Chinese Academy of Sciences.

Keywords

Blind deconvolution, Framelet, Generalized cross validation, Iterative methods, Total variation

Publication Date

2012

Source Publication Title

Journal of Computational Mathematics -International Edition-

Volume

30

Issue

1

Start Page

80

End Page

100

Publisher

Science Press

ISSN (print)

02549409

ISSN (electronic)

19917139

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