A Nonstandard Higher-Order Variational Model for Speckle Noise Removal and Thin-Structure Detection

A Nonstandard Higher-Order Variational Model for Speckle Noise Removal and Thin-Structure Detection

Year:    2019

Author:    Hamdi Houichet, Anis Theljani, Badreddine Rjaibi, Maher Moakher

Journal of Mathematical Study, Vol. 52 (2019), Iss. 4 : pp. 394–424

Abstract

We propose a multiscale approach for a nonstandard higher-order PDE based on the $p$(·)-Kirchhoff energy. We first use the topological gradient approach for a semi-linear case in order to detect important objects of the image. We consider a fully nonlinear $p$(·)-Kirchhoff equation with variable-exponent functions that are chosen adaptively based on the map provided by the topological gradient in order to preserve important features of the image. Then, we consider the split Bregman method for the numerical implementation of the proposed model. We compare our model with other classical variational approaches such as the TVL and bi-harmonic restoration models. Finally, we present some numerical results to illustrate the effectiveness of our approach.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/jms.v52n4.19.03

Journal of Mathematical Study, Vol. 52 (2019), Iss. 4 : pp. 394–424

Published online:    2019-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    31

Keywords:    Inverse problems regularization procedures $p$(·)-Kirchhoff topological gradient split Bregman.

Author Details

Hamdi Houichet

Anis Theljani

Badreddine Rjaibi

Maher Moakher