基于自适应投影算法的分数阶全变分去噪模型<sup>*</sup>

doi:10.16451/j.cnki.issn1003-6059.201611006

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Abstract To preserve weak edges and texture details of an image during image denoising, a fractional order total variation denoising model is presented based on adaptive projection algorithm. Firstly, Grünwald-Letnikov fractional order differential is used as a substitute for the first order derivative in the regularization term of total variation model. Secondly, the image is projected to a total variation ball to handle the optimization problem. The image is divided into the texture area and the non-texture area according to the local information of the image, and thus soft threshold values can be calculated adaptively. Both theoretical analysis and experimental results show that the proposed method eliminates the block effect as well as preserves the texture details effectively for removing noise.

Key words： Image Denoising Fractional Differential Total Variation Projection Algorithm

Received: 20 April 2016

ZTFLH:

TP 391.41

Fund:Supported by National Natural Science Foundation of China (No.61462065,61263046), Natural Science Foundation of Jiangxi Province (No.20151BAB207036)

About author:: ZHANG Guimei, born in 1970, Ph.D., professor. Her research interests include computer vision, image processing and pattern recognition.
SUN Xiaoxu, born in 1992, master student. His research interests include computer vision, image processing and pattern recognition.
LIU JianxinCorresponding author, born in 1969, Ph.D., professor. His research interests include computer vision and intelligent robot.

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	ZHANG Guimei
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Cite this article:

ZHANG Guimei,SUN Xiaoxu,LIU Jianxin. Fractional Total Variation Denoising Model Based on Adaptive Projection Algorithm[J]. , 2016, 29(11): 1009-1018.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201611006 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2016/V29/I11/1009

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