A Total Variational Approach Based on Meridian Norm for Restoring Noisy Images with Alpha-stable Noise
YANG Zhenzhen①② YANG Zhen② LI Lei① JIN Zhengmeng①
①(Center for Visual Cognitive Computation and Application, Nanjing University of Posts and Telecommunications, Nanjing 210023, China) ②(Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, Nanjing University of Posts and Telecommunications, Nanjing 210003, China)
In actual applications, noises may inevitably exist, and thus to study the denoising method for images is great significant task in image processing filed that attracts much attention in recent years. In this paper, based on the statistical property of Meridian distributed and the Total Variational (TV), a total variational method is proposed for restoring images degraded by alpha-stable noise. Besides, in order to obtain a strictly convex model, a quadratic penalty term is added, which guarantees the uniqueness of the solution. For solving the novel convex variational model, a primal-dual algorithm is employed to solve the above model, and the convergence of the algorithm is proved. The experimental results demonstrate that the feasibility and effectiveness of the proposed model for the noisy images with alpha-stable noise.
杨真真,杨震, 李雷,金正猛. Alpha稳态噪声下基于Meridian范数的全变分图像去噪算法[J]. 电子与信息学报, 2017, 39(5): 1109-1115.
YANG Zhenzhen, YANG Zhen, LI Lei, JIN Zhengmeng. A Total Variational Approach Based on Meridian Norm for Restoring Noisy Images with Alpha-stable Noise. JEIT, 2017, 39(5): 1109-1115.
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