Alpha稳态噪声下基于Meridian范数的全变分图像去噪算法

doi:10.11999/JEIT160657

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Abstract

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.

Key words： Image processing Meridian norm Alpha-stable noise Primal-dual algorithm Total Variational (TV)

Received: 21 June 2016 Published: 24 February 2017

PACS:

TN911.73

Fund:

The National Natural Science Foundation of China (61501251, 61271335, 61271240), The Natural Science Foundation of Jiangsu Province (BK20140891), The Science Foundation of Nanjing University of Posts and Telecommunications (NY214191)

Corresponding Authors: YANG Zhenzhen E-mail: yangzz@njupt.edu.cn

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	YANG Zhenzhen
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	JIN Zhengmeng

Cite this article:

YANG Zhenzhen,YANG Zhen,LI Lei等. A Total Variational Approach Based on Meridian Norm for Restoring Noisy Images with Alpha-stable Noise[J]. JEIT, 2017, 39(5): 1109-1115.

URL:

http://jeit.ie.ac.cn/EN/10.11999/JEIT160657 OR http://jeit.ie.ac.cn/EN/Y2017/V39/I5/1109

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