JISE


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Journal of Information Science and Engineering, Vol. 32 No. 3, pp. 747-762


An Adaptive Fractional-Order Variation Method for Multiplicative Noise Removal

DAN TIAN1,2, YINGKUI DU1,2 AND DALI CHEN2 
1Department of Information Engineering 
Shenyang University 
Shenyang, 110044 P.R. China 
2State key Laboratory of Robotics 
Shenyang Institute of Automation 
Chinese Academy of Sciences 
Shenyang, 110016 P.R. China 
E-mail: www.sltd2008@163.com

    This paper aims to develop a convex fractional-order variation model for image multiplicative noise removal, where the regularization parameter can be adjusted adaptively according to balancing principle at each iterations to control the trade-off between the fitness and smoothness of the denoised images. In the light of the saddle-point theory, a primal-dual algorithm has been applied to solve the proposed model, and the convergence of the algorithm is guaranteed. Simulations with comparisons are carried out to demonstrate the details preserving ability and the fast property of our proposed denoising method.

Keywords: gamma noise, image denoising, fractional differential, primal-dual algorithm, adaptive regularization parameter

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