A denoising PDE model based on isotropic diffusion and total variation models

Mohamadi, Neda; Soheili, Ali Reza; Toutounian, Faezeh

doi:10.22034/cmde.2020.26116.1331

A denoising PDE model based on isotropic diffusion and total variation models

Document Type : Research Paper

Authors

¹ Department of Mathematics and statistics, Mashhad Branch, Islamic Azad University, Mashhad, Iran.

² Department of Applied Mathematics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iran.

10.22034/cmde.2020.26116.1331

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