Year: 2013
East Asian Journal on Applied Mathematics, Vol. 3 (2013), Iss. 4 : pp. 263–282
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.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/eajam.240713.120813a
East Asian Journal on Applied Mathematics, Vol. 3 (2013), Iss. 4 : pp. 263–282
Published online: 2013-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 20
Keywords: Convex model image deblurring multiplicative noise Split-Bregman Algorithm total variation variational model.
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