<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In this paper, we propose a novel hybrid model for restoration of images corrupted by multiplicative noise. Using a MAP estimator, we can derive a functional whose minimizer corresponds to the denoised image we want to recover. The energies studied here are inspired by image restoration with non linear variable exponent [1, 2], and it is a combination of fast growth with respect to low gradient and slow growth when the gradient is large. We study a mathematical framework to prove the well posedness of the minimizer problem and we introduce the associated evolution problem, for which we derive numerical approaches. At last, compared experimental results distinctly demonstrate the superiority of the proposed model, in term of removing some muliplicative noise while preserving the edges and reducing the staircase effect.</p></abstract>

In this paper, we propose a novel hybrid model for restoration of images corrupted by multiplicative noise. Using a MAP estimator, we can derive a functional whose minimizer corresponds to the denoised image we want to recover. The energies studied here are inspired by image restoration with non linear variable exponent [1, 2], and it is a combination of fast growth with respect to low gradient and slow growth when the gradient is large. We study a mathematical framework to prove the well posedness of the minimizer problem and we introduce the associated evolution problem, for which we derive numerical approaches. At last, compared experimental results distinctly demonstrate the superiority of the proposed model, in term of removing some muliplicative noise while preserving the edges and reducing the staircase effect.

An Efficient Algorithm for Reconstruction Images Corrupted by Some Multiplicative Noises

Moroccan Journal of Pure and Applied Analysis

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

In this paper, we propose a novel hybrid model for restoration of images corrupted by multiplicative noise. Using a MAP estimator, we can derive a functional...

An Efficient Algorithm for Reconstruction Images Corrupted by Some Multiplicative Noises

Online veröffentlicht: 24. Jan. 2020

Seitenbereich: 263 - 278

Eingereicht: 05. Okt. 2019

Akzeptiert: 24. Dez. 2019

DOI: https://doi.org/10.2478/mjpaa-2019-0019

Schlüsselwörter
Multiplicative noise, Total variation, Image restoration, Nonlinear energy, Variable exponent, Numerical algorithm

© 2019 L. Ziad et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

An Efficient Algorithm for Reconstruction Images Corrupted by Some Multiplicative Noises

Online veröffentlicht: 24. Jan. 2020

Seitenbereich: 263 - 278

Eingereicht: 05. Okt. 2019

Akzeptiert: 24. Dez. 2019

DOI: https://doi.org/10.2478/mjpaa-2019-0019

SchlüsselwörterMultiplicative noise, Total variation, Image restoration, Nonlinear energy, Variable exponent, Numerical algorithm

© 2019 L. Ziad et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Multiplicative noise, Total variation, Image restoration, Nonlinear energy, Variable exponent, Numerical algorithm