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2013 Fractional-Order Total Variation Image Restoration Based on Primal-Dual Algorithm
Dali Chen, YangQuan Chen, Dingyu Xue
Abstr. Appl. Anal. 2013(SI25): 1-10 (2013). DOI: 10.1155/2013/585310


This paper proposes a fractional-order total variation image denoising algorithm based on the primal-dual method, which provides a much more elegant and effective way of treating problems of the algorithm implementation, ill-posed inverse, convergence rate, and blocky effect. The fractional-order total variation model is introduced by generalizing the first-order model, and the corresponding saddle-point and dual formulation are constructed in theory. In order to guarantee O1/N2 convergence rate, the primal-dual algorithm was used to solve the constructed saddle-point problem, and the final numerical procedure is given for image denoising. Finally, the experimental results demonstrate that the proposed methodology avoids the blocky effect, achieves state-of-the-art performance, and guarantees O1/N2 convergence rate.


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Dali Chen. YangQuan Chen. Dingyu Xue. "Fractional-Order Total Variation Image Restoration Based on Primal-Dual Algorithm." Abstr. Appl. Anal. 2013 (SI25) 1 - 10, 2013.


Published: 2013
First available in Project Euclid: 26 February 2014

zbMATH: 1364.94091
Digital Object Identifier: 10.1155/2013/585310

Rights: Copyright © 2013 Hindawi

Vol.2013 • No. SI25 • 2013
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