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The Convex Relaxation Method on Deconvolution Model withMultiplicative Noise

Published online by Cambridge University Press:  03 June 2015

Yumei Huang
Affiliation:
School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000, China
Michael Ng
Affiliation:
Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong
Tieyong Zeng*
Affiliation:
Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong
*
*Corresponding author.Email:zeng@hkbu.edu.hk
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Abstract

In this paper, we consider variational approaches to handle the multiplicative noise removal and deblurring problem. Based on rather reasonable physical blurring-noisy assumptions, we derive a new variational model for this issue. After the study of the basic properties, we propose to approximate it by a convex relaxation model which is a balance between the previous non-convex model and a convex model. The relaxed model is solved by an alternating minimization approach. Numerical examples are presented to illustrate the effectiveness and efficiency of the proposed method.

Type
Research Article
Copyright
Copyright © Global Science Press Limited 2013

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The Convex Relaxation Method on Deconvolution Model withMultiplicative Noise
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