Multiplicative Noise Removal via a Novel Variational Model. (27th June 2010)

• Record Type: Journal Article
• Authors: Huang, Li-Li; Xiao, Liang; Wei, Zhi-Hui
• Other Names: Zhang Lei Academic Editor.
• Is Part Of: EURASIP journal on image and video processing. Volume 2010(2010)
• Publication Date: 2010-06-27
• Subjects: Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; Traitement d'images; Vidéo numérique; Digital video; Image processing -- Digital techniques; Periodicals; Electronic journal; Electronic journals; 621.367
• DOI: 10.1155/2010/250768
• Languages: English
• ISSNs: 1687-5176

Abstract

Abstract : Multiplicative noise appears in various image processing applications, such as synthetic aperture radar, ultrasound imaging, single particle emission-computed tomography, and positron emission tomography. Hence multiplicative noise removal is of momentous significance in coherent imaging systems and various image processing applications. This paper proposes a nonconvex Bayesian type variational model for multiplicative noise removal which includes the total variation (TV) and the Weberized TV as regularizer. We study the issues of existence and uniqueness of a minimizer for this variational model. Moreover, we develop a linearized gradient method to solve the associated Euler-Lagrange equation via a fixed-point iteration. Our experimental results show that the proposed model has good performance.