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Salt and Pepper Noise Removal Method Based on the Edge-Adaptive Total Variation Model

Authors :
Yunyun Jiang
Hefei Wang
Yi Cai
Bo Fu
Source :
Frontiers in Applied Mathematics and Statistics, Vol 8 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

The traditional median filter can handle the image salt and pepper noise better. However, when the noise intensity is large, it is often necessary to enlarge the filter window to ensure the denoising effect, but the enlarged window may also cause excessive smoothing of the image, loss of texture details, and blurred edges. In view of the strong edge preservation characteristics of variational model denoising, we propose a salt and pepper noise removal method based on the edge-adaptive total variational model. Firstly, the image is segmented into edge regions and non-edge regions by edge detection operators. Secondly, the salt and pepper noise of the image is processed using the median filter and adaptive total variation model, respectively. Lastly, the non-edge regions processed by the median filter and the edge regions processed by the adaptive total variation model are extracted for splicing. The experimental results show that the method cannot only effectively remove salt and pepper noise, but also effectively protect the main edge details of the image.

Details

Language :
English
ISSN :
22974687
Volume :
8
Database :
Directory of Open Access Journals
Journal :
Frontiers in Applied Mathematics and Statistics
Publication Type :
Academic Journal
Accession number :
edsdoj.385cfe9480142d69b41a7ca0f4d1a32
Document Type :
article
Full Text :
https://doi.org/10.3389/fams.2022.918357