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Multiplicative Noise Removal via a Novel Variational Model

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Author(s): Huang Li-Li | Xiao Liang | Wei Zhi-Hui

Journal: EURASIP Journal on Image and Video Processing
ISSN 1687-5176

Volume: 2010;
Issue: 1;
Start page: 250768;
Date: 2010;
Original page

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.
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