Total variation image restoration algorithm based on prior information

被引：0
|
作者：
Zhang J. [1 ,2 ,3 ]
Luo L. [1 ,2 ,3 ]
Shu H. [1 ,2 ,3 ]
Wu J. [1 ,2 ,3 ]
机构：
[1] School of Computer Science and Engineering, Southeast University, Nanjing
[2] Key Laboratory of Computer Network and Information Integration of Ministry of Education, Southeast University, Nanjing
[3] Centre de Recherche en Information Biomédicale Sino-Francais, Southeast University, Nanjing
来源：
Dongnan Daxue Xuebao | / 6卷 / 1132-1136期
关键词：
Image restoration; Nonlocal mean; Prior information; Split Bregman; Total variation;
D O I：
10.3969/j.issn.1001-0505.2016.06.004
中图分类号：
学科分类号：
摘要：
In order to improve the performance of image restoration of the total variation (TV) model, an improved TV image restoration algorithm based on prior information is proposed. First, the nonlocal means (NLM) filtering algorithm, which can effectively protect the structural information of the filtered image, is employed to reduce the noise within the image to restore. Thus, the filtered prior image information is obtained. Then, an improved total variation restoration model based on the obtained prior information is established. The proposed model can not only maintain the TV model' advantage of protecting the boundary information of restorated image, but also maintain the NLM model' advantage of protecting the structure information. Finally, the proposed model is optimized by the split Bregman alternating direction multiplier iteration algorithm and the restored image is obtained. The experimental results show that compared with other algorithms, the proposed algorithm achieves better restoration effect in terms of the subjective visual effect and the objective quantitative indices such as peak signal to noise ratio (PSNR) and structural similarity (SSIM). © 2016, Editorial Department of Journal of Southeast University. All right reserved.
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页码：1132 / 1136
页数：4
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