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2014 A Total Variation Model Based on the Strictly Convex Modification for Image Denoising
Boying Wu, Elisha Achieng Ogada, Jiebao Sun, Zhichang Guo
Abstr. Appl. Anal. 2014(SI71): 1-16 (2014). DOI: 10.1155/2014/948392


We propose a strictly convex functional in which the regular term consists of the total variation term and an adaptive logarithm based convex modification term. We prove the existence and uniqueness of the minimizer for the proposed variational problem. The existence, uniqueness, and long-time behavior of the solution of the associated evolution system is also established. Finally, we present experimental results to illustrate the effectiveness of the model in noise reduction, and a comparison is made in relation to the more classical methods of the traditional total variation (TV), the Perona-Malik (PM), and the more recent D-α-PM method. Additional distinction from the other methods is that the parameters, for manual manipulation, in the proposed algorithm are reduced to basically only one.


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Boying Wu. Elisha Achieng Ogada. Jiebao Sun. Zhichang Guo. "A Total Variation Model Based on the Strictly Convex Modification for Image Denoising." Abstr. Appl. Anal. 2014 (SI71) 1 - 16, 2014.


Published: 2014
First available in Project Euclid: 6 October 2014

zbMATH: 07023375
MathSciNet: MR3226244
Digital Object Identifier: 10.1155/2014/948392

Rights: Copyright © 2014 Hindawi


Vol.2014 • No. SI71 • 2014
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