Affiliation:
1. Department of Mathematics, School of Basic Sciences and Research, Sharda University, Noida-201310, U.P., India
Abstract
Background:
In the image processing area, deblurring and denoising are the most challenging
hurdles. The deblurring image by a spatially invariant kernel is a frequent problem in the
field of image processing.
Methods:
For deblurring and denoising, the total variation (TV norm) and nonlinear anisotropic
diffusion models are powerful tools. In this paper, nonlinear anisotropic diffusion models for image
denoising and deblurring are proposed. The models are developed in the following manner: first
multiplying the magnitude of the gradient in the anisotropic diffusion model, and then apply priori
smoothness on the solution image by Gaussian smoothing kernel.
Results:
The finite difference method is used to discretize anisotropic diffusion models with forward-
backward diffusivities.
Conclusion:
The results of the proposed model are given in terms of the improvement.
Publisher
Bentham Science Publishers Ltd.
Subject
Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials
Cited by
6 articles.
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