A convex relaxation method for computing exact global solutions for multiplicative noise removal

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:238

Article

Liu, Chunxiao²  Zhu, Shengfeng¹ 

[1] E China Normal Univ, Dept Math, Shanghai 200241, Peoples R China

[2] Hangzhou Normal Univ, Dept Math, Hangzhou 310036, Zhejiang, Peoples R China

关键词: Multiplicative noise;    Image denoising;    Total variation;    Global minimization;    Primal-dual;   

DOI  :  10.1016/j.cam.2012.08.019

来源: Elsevier

【 摘 要 】

We propose a convex relaxation technique for computing global solutions for the nonconvex multiplicative noise model. The method is based on functional lifting by introducing an additional dimension. We employ a primal-dual-based gradient-type algorithm in numerical implementations to overcome the nondifferentiability of the total variation term. Numerical results show that our algorithm is highly efficient. Furthermore, global solutions of the original model can be obtained with no dependence on the initial guess. (C) 2012 Elsevier B.V. All rights reserved.

【 授权许可】

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