A Weberized Total Variation Regularization-Based Image Multiplicative Noise Removal Algorithm. (12th May 2010)

• Record Type: Journal Article
• Authors: Xiao Xiao, Liang Liang; Huang Huang, Li-Li Li-Li; Wei Wei, Zhi-Hui Zhi-Hui
• Other Names: Becerikli Becerikli Yasar Yasar Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2010(2010)
• Publication Date: 2010-05-12
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2010/490384
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : Multiplicative noise removal is of momentous significance in coherent imaging systems and various image processing applications. This paper proposes a new nonconvex variational model for multiplicative noise removal under the Weberized total variation (TV) regularization framework. Then, we propose and investigate another surrogate strictly convex objective function for Weberized TV regularization-based multiplicative noise removal model. Finally, we propose and design a novel way of fast alternating optimizing algorithm which contains three subminimizing parts and each of them permits a closed-form solution. Our experimental results show that our algorithm is effective and efficient to filter out multiplicative noise while well preserving the feature details.