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2013 | 11 | 10 | 1414-1422
Article title

Fractional-order TV-L2 model for image denoising

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EN
Abstracts
EN
This paper proposes a new fractional order total variation (TV) denoising method, which provides a much more elegant and effective way of treating problems of the algorithm implementation, ill-posed inverse, regularization parameter selection and blocky effect. Two fractional order TV-L2 models are constructed for image denoising. The majorization-minimization (MM) algorithm is used to decompose these two complex fractional TV optimization problems into a set of linear optimization problems which can be solved by the conjugate gradient algorithm. The final adaptive numerical procedure is given. Finally, we report experimental results which show that the proposed methodology avoids the blocky effect and achieves state-of-the-art performance. In addition, two medical image processing experiments are presented to demonstrate the validity of the proposed methodology.
Publisher

Journal
Year
Volume
11
Issue
10
Pages
1414-1422
Physical description
Dates
published
1 - 10 - 2013
online
19 - 12 - 2013
Contributors
author
  • Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping Districe, 110819, Shenyang, Liaoning, China, chendali@ise.neu.edu.cn
author
  • Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping Districe, 110819, Shenyang, Liaoning, China
  • Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping Districe, 110819, Shenyang, Liaoning, China
author
  • MESA Lab, University of California, Merced, 5200 North Lake Road, Merced, CA, 95343, USA
author
  • Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping Districe, 110819, Shenyang, Liaoning, China
References
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.-psjd-doi-10_2478_s11534-013-0241-1
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