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Title: Hybrid fuzzy logic and gravitational search algorithm-based multiple filters for image restoration

Authors: A. Senthilselvi; R. Sukumar; S. Senthilpandi

Addresses: Department of Computer Science and Engineering, Sethu Institute of Technology, Virudhunagar, India ' Department of Computer Science and Engineering, School of Engineering and Technology, Jain University, JGI Global Campus, Jakkasandra post, Kanakapura Taluk, Karnataka, India ' Department of Information Technology, Sethu Institute of Technology, Virudhunagar, India

Abstract: In this paper, we present a multiple image filters for removal of impulse noises from test images. It utilises fuzzy logic (FL) approach to design a noise detector (ND) optimised by gravitational search algorithm (GSA) and utilises median filter (MF) for restoring. The proposed multiple filters used the FL approach to detect each pixels of a tests image are noise corrupted or not. If it is considered as noise-corrupted, the multiple filters restore it with the MF filter. Otherwise, it remains unchanged. We split the image into number of windows and each window apply the multiple filters. The filter output is used for the rule generation. The optimal rules are selected using GSA and given to the fuzzy logic system to detect the noise pixel. The experimental results are carried out using different noise level and different methods. The performance measured in terms of PSNR, MSE and visual quality.

Keywords: image restoration; impulse noise; fuzzy logic; multiple filters; median filter; standard test images; gravitational search algorithm; GSA.

DOI: 10.1504/IJDATS.2020.105182

International Journal of Data Analysis Techniques and Strategies, 2020 Vol.12 No.1, pp.76 - 97

Received: 12 Oct 2017
Accepted: 26 Sep 2018

Published online: 10 Feb 2020 *

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