Computational Methods for Differential Equations, Volume (8), No (4), Year (2020-11) , Pages (815-826)

Title : ( A denoising PDE model based on isotropic diffusion and total variation models )

Authors: Ali Reza Soheili , neda mohamadi , Faezeh Toutounian Mashhad ,

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Abstract

In this paper, a denoising PDE model based on a combination of the isotropic diffusion and total variation models is presented. The new weighted model is able to be adaptive in each region in accordance with the image’s information. The model performs more diffusion in the flat regions of the image, and less diffusion in the edges of the image. The new model has more ability to restore the image in terms of peak signal to noise ratio and visual quality, compared with total variation, isotropic diffusion, and some well-known models. Experimental results show that the model is able to suppress the noise effectively while preserving texture features and edge information well.

Keywords

, Image Denoising, Isotropic Diffusion, Total Variation, Partial Differential Equation
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@article{paperid:1070655,
author = {Soheili, Ali Reza and Mohamadi, Neda and Toutounian Mashhad, Faezeh},
title = {A denoising PDE model based on isotropic diffusion and total variation models},
journal = {Computational Methods for Differential Equations},
year = {2020},
volume = {8},
number = {4},
month = {November},
issn = {2345-3982},
pages = {815--826},
numpages = {11},
keywords = {Image Denoising; Isotropic Diffusion; Total Variation; Partial Differential Equation},
}

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%0 Journal Article
%T A denoising PDE model based on isotropic diffusion and total variation models
%A Soheili, Ali Reza
%A Mohamadi, Neda
%A Toutounian Mashhad, Faezeh
%J Computational Methods for Differential Equations
%@ 2345-3982
%D 2020

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