Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

Non-Lipschitz lp-regularization and box constrained model for image restoration

Language

English

Abstract

Nonsmooth nonconvex regularization has remarkable advantages for the restoration of piecewise constant images. Constrained optimization can improve the image restoration using a priori information. In this paper, we study regularized nonsmooth nonconvex minimization with box constraints for image restoration. We present a computable positive constant θ for using nonconvex nonsmooth regularization, and show that the difference between each pixel and its four adjacent neighbors is either 0 or larger than θ in the recovered image. Moreover, we give an explicit form of θ for the box-constrained image restoration model with the non-Lipschitz nonconvex l p-norm (0

Keywords

Box constraints, image restoration, non-Lipschitz, nonsmooth and nonconvex, regularization

Publication Date

2012

Source Publication Title

IEEE Transactions on Image Processing

Volume

21

Issue

12

Start Page

4709

End Page

4721

Publisher

Institute of Electrical and Electronics Engineers

DOI

10.1109/TIP.2012.2214051

Link to Publisher's Edition

http://dx.doi.org/10.1109/TIP.2012.2214051

ISSN (print)

10577149

ISSN (electronic)

19410042

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