Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter

In the data collection phase, the digital images are captured using sensors that often contaminated by noise (undesired random signal). In digital image processing task, enhancing the image quality and reducing the noise is a central process. Image denoising effectively preserves the image edges to...

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Autores principales:	Suneetha Akula, Srinivasa Reddy E.
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2020
Materias:	denoising digital image processing fuzzy filter fuzzy logic gaussian noise Science Q Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/0d1f62fde714442f9450a79f671732ca
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id	oai:doaj.org-article:0d1f62fde714442f9450a79f671732ca
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spelling	oai:doaj.org-article:0d1f62fde714442f9450a79f671732ca2021-12-05T14:10:51ZRobust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter2191-026X10.1515/jisys-2019-0211https://doaj.org/article/0d1f62fde714442f9450a79f671732ca2020-08-01T00:00:00Zhttps://doi.org/10.1515/jisys-2019-0211https://doaj.org/toc/2191-026XIn the data collection phase, the digital images are captured using sensors that often contaminated by noise (undesired random signal). In digital image processing task, enhancing the image quality and reducing the noise is a central process. Image denoising effectively preserves the image edges to a higher extend in the flat regions. Several adaptive filters (median filter, Gaussian filter, fuzzy filter, etc.) have been utilized to improve the smoothness of digital image, but these filters failed to preserve the image edges while removing noise. In this paper, a modified fuzzy set filter has been proposed to eliminate noise for restoring the digital image. Usually in fuzzy set filter, sixteen fuzzy rules are generated to find the noisy pixels in the digital image. In modified fuzzy set filter, a set of twenty-four fuzzy rules are generated with additional four pixel locations for determining the noisy pixels in the digital image. The additional eight fuzzy rules ease the process of finding the image pixels,whether it required averaging or not. In this scenario, the input digital images were collected from the underwater photography fish dataset. The efficiency of the modified fuzzy set filter was evaluated by varying degrees of Gaussian noise (0.01, 0.03, and 0.1 levels of Gaussian noise). For performance evaluation, Structural Similarity (SSIM), Mean Structural Similarity (MSSIM), Mean Square Error (MSE), Normalized Mean Square Error (NMSE), Universal Image Quality Index (UIQI), Peak Signal to Noise Ratio (PSNR), and Visual Information Fidelity (VIF) were used. The experimental results showed that the modified fuzzy set filter improved PSNR value up to 2-3 dB, MSSIM up to 0.12-0.03, and NMSE value up to 0.38-0.1 compared to the traditional filtering techniques.Suneetha AkulaSrinivasa Reddy E.De Gruyterarticledenoisingdigital image processingfuzzy filterfuzzy logicgaussian noiseScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 240-257 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	denoising digital image processing fuzzy filter fuzzy logic gaussian noise Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	denoising digital image processing fuzzy filter fuzzy logic gaussian noise Science Q Electronic computers. Computer science QA75.5-76.95 Suneetha Akula Srinivasa Reddy E. Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter
description	In the data collection phase, the digital images are captured using sensors that often contaminated by noise (undesired random signal). In digital image processing task, enhancing the image quality and reducing the noise is a central process. Image denoising effectively preserves the image edges to a higher extend in the flat regions. Several adaptive filters (median filter, Gaussian filter, fuzzy filter, etc.) have been utilized to improve the smoothness of digital image, but these filters failed to preserve the image edges while removing noise. In this paper, a modified fuzzy set filter has been proposed to eliminate noise for restoring the digital image. Usually in fuzzy set filter, sixteen fuzzy rules are generated to find the noisy pixels in the digital image. In modified fuzzy set filter, a set of twenty-four fuzzy rules are generated with additional four pixel locations for determining the noisy pixels in the digital image. The additional eight fuzzy rules ease the process of finding the image pixels,whether it required averaging or not. In this scenario, the input digital images were collected from the underwater photography fish dataset. The efficiency of the modified fuzzy set filter was evaluated by varying degrees of Gaussian noise (0.01, 0.03, and 0.1 levels of Gaussian noise). For performance evaluation, Structural Similarity (SSIM), Mean Structural Similarity (MSSIM), Mean Square Error (MSE), Normalized Mean Square Error (NMSE), Universal Image Quality Index (UIQI), Peak Signal to Noise Ratio (PSNR), and Visual Information Fidelity (VIF) were used. The experimental results showed that the modified fuzzy set filter improved PSNR value up to 2-3 dB, MSSIM up to 0.12-0.03, and NMSE value up to 0.38-0.1 compared to the traditional filtering techniques.
format	article
author	Suneetha Akula Srinivasa Reddy E.
author_facet	Suneetha Akula Srinivasa Reddy E.
author_sort	Suneetha Akula
title	Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter
title_short	Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter
title_full	Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter
title_fullStr	Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter
title_full_unstemmed	Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter
title_sort	robust gaussian noise detection and removal in color images using modified fuzzy set filter
publisher	De Gruyter
publishDate	2020
url	https://doaj.org/article/0d1f62fde714442f9450a79f671732ca
work_keys_str_mv	AT suneethaakula robustgaussiannoisedetectionandremovalincolorimagesusingmodifiedfuzzysetfilter AT srinivasareddye robustgaussiannoisedetectionandremovalincolorimagesusingmodifiedfuzzysetfilter
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Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter

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