TAILIEUCHUNG - Báo cáo sinh học: " Research Article Multiplicative Noise Removal via a Novel Variational Model"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Research Article Multiplicative Noise Removal via a Novel Variational Model | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2010 Article ID 250768 16 pages doi 2010 250768 Research Article Multiplicative Noise Removal via a Novel Variational Model Li-Li Huang 1 2 Liang Xiao 1 and Zhi-Hui Wei3 1 School of Computer Science and Technology Nanjing University of Science and Technology Nanjing 210094 China 2 Department of Information and Computing Science Guangxi University of Technology Liuzhou 545006 China 3 Department of Applied Mathematics Nanjing University of Science and Technology Nanjing 210094 China Correspondence should be addressed to Liang Xiao xiaoliang@ Received 30 March 2010 Revised 5 May 2010 Accepted 2 June 2010 Academic Editor Lei Zhang Copyright 2010 Li-Li Huang et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 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. 1. Introduction Image denoising is an inverse problem widely studied in signal and image processing fields. The problem includes additive noise removal and multiplicative noise removal. In many image formation

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