A total variable-order variation model for image denoising

In this paper,we explore a new variational model based on the fractional derivative and total variation.Due to some metrics,our approach shows great results compared to other competitive models.In particular,deleting the noise and preserving edges,features and corners are headlights to our approach....

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Bibliographic Details
Published inAIMS mathematics Vol. 4; no. 5; pp. 1320 - 1335
Main Authors Hakim, Abdelilah, Ben-Loghfyry, Anouar
Format Journal Article
LanguageEnglish
Published AIMS Press 01.01.2019
Subjects
finite difference
fractional derivative
image denoising
primal dual
total variation
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ISSN2473-6988
2473-6988
DOI10.3934/math.2019.5.1320

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Summary:In this paper,we explore a new variational model based on the fractional derivative and total variation.Due to some metrics,our approach shows great results compared to other competitive models.In particular,deleting the noise and preserving edges,features and corners are headlights to our approach.For the fractional variable-order derivatives,different discretizations were presented to comparison.The theoretical results are validated by the Primal Dual Projected Gradient (PDPG) Algorithm which is well adapted to the fractional calculus.
ISSN:2473-6988
2473-6988
DOI:10.3934/math.2019.5.1320