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An adaptive model combining a total variation filter and a fractional-order filter for image restoration
Author(s) -
Yang Yafeng,
Zhao Donghong
Publication year - 2019
Publication title -
journal of algorithms and computational technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.234
H-Index - 13
eISSN - 1748-3026
pISSN - 1748-3018
DOI - 10.1177/1748301819833054
Subject(s) - filter (signal processing) , mathematics , algorithm , image restoration , image (mathematics) , adaptive filter , dual (grammatical number) , composite image filter , noise (video) , filter design , basis (linear algebra) , kernel adaptive filter , computer science , artificial intelligence , image processing , computer vision , literature , art , geometry
In this paper, we propose a model that combines a total variation filter with a fractional-order filter, which can unite the advantages of the two filters, and has a remarkable effect in the protection of image edges and texture details; simultaneously, the proposed model can eliminate the staircase effect. In addition, the model improves the PSNR compared with the total variation filter and the fractional-order filter when removing noise. Zhu and Chan presented the primal-dual hybrid gradient algorithm and proved that it is effective for the total variation filter. On the basis of their work, we employ the primal-dual hybrid gradient algorithm to solve the combined model in this article. The final experimental results show that the new model and algorithm are effective for image restoration.

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