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New Hybrid Variational Recovery Model for Blurred Images with Multiplicative Noise

Published online by Cambridge University Press:  28 May 2015

Yiqiu Dong  and
Tieyong Zeng
Yiqiu Dong*
Affiliation:
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark
Tieyong Zeng*
Affiliation:
Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong
*
Corresponding author. Email Address: [email protected]
Corresponding author. Email Address: [email protected]
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Abstract

A new hybrid variational model for recovering blurred images in the presence of multiplicative noise is proposed. Inspired by previous work on multiplicative noise removal, an I-divergence technique is used to build a strictly convex model under a condition that ensures the uniqueness of the solution and the stability of the algorithm. A split-Bregman algorithm is adopted to solve the constrained minimisation problem in the new hybrid model efficiently. Numerical tests for simultaneous deblurring and denoising of the images subject to multiplicative noise are then reported. Comparison with other methods clearly demonstrates the good performance of our new approach.

Keywords

52A4165K0565K1590C2590C30Convex modelimage deblurringmultiplicative noiseSplit-Bregman Algorithmtotal variationvariational model
Type
Research Article
Information
East Asian Journal on Applied Mathematics , Volume 3 , Issue 4 , November 2013 , pp. 263 - 282
Copyright
Copyright © Global-Science Press 2013

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