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New Real-Time Impulse Noise Removal Method Applied to Chest X-ray Images

In this paper, we propose a new Modified Laplacian Vector Median Filter (MLVMF) for real-time denoising complex images corrupted by “salt and pepper” impulsive noise. The method consists of two rounds with three steps each: the first round starts with the identification of pixels that may be contami...

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Autores principales: Rashid, Nasr, Berriri, Kamel, Albekairi, Mohammed, Kaaniche, Khaled, Ben Atitallah, Ahmed, Khan, Muhammad Attique, El-Hamrawy, Osama I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689277/
https://www.ncbi.nlm.nih.gov/pubmed/36359581
http://dx.doi.org/10.3390/diagnostics12112738
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author Rashid, Nasr
Berriri, Kamel
Albekairi, Mohammed
Kaaniche, Khaled
Ben Atitallah, Ahmed
Khan, Muhammad Attique
El-Hamrawy, Osama I.
author_facet Rashid, Nasr
Berriri, Kamel
Albekairi, Mohammed
Kaaniche, Khaled
Ben Atitallah, Ahmed
Khan, Muhammad Attique
El-Hamrawy, Osama I.
author_sort Rashid, Nasr
collection PubMed
description In this paper, we propose a new Modified Laplacian Vector Median Filter (MLVMF) for real-time denoising complex images corrupted by “salt and pepper” impulsive noise. The method consists of two rounds with three steps each: the first round starts with the identification of pixels that may be contaminated by noise using a Modified Laplacian Filter. Then, corrupted pixels pass a neighborhood-based validation test. Finally, the Vector Median Filter is used to replace noisy pixels. The MLVMF uses a 5 × 5 window to observe the intensity variations around each pixel of the image with a rotation step of π/8 while the classic Laplacian filters often use rotation steps of π/2 or π/4. We see better identification of noise-corrupted pixels thanks to this rotation step refinement. Despite this advantage, a high percentage of the impulsive noise may cause two or more corrupted pixels (with the same intensity) to collide, preventing the identification of noise-corrupted pixels. A second round is then necessary using a second set of filters, still based on the Laplacian operator, but allowing focusing only on the collision phenomenon. To validate our method, MLVMF is firstly tested on standard images, with a noise percentage varying from 3% to 30%. Obtained performances in terms of processing time, as well as image restoration quality through the PSNR (Peak Signal to Noise Ratio) and the NCD (Normalized Color Difference) metrics, are compared to the performances of VMF (Vector Median Filter), VMRHF (Vector Median-Rational Hybrid Filter), and MSMF (Modified Switching Median Filter). A second test is performed on several noisy chest x-ray images used in cardiovascular disease diagnosis as well as COVID-19 diagnosis. The proposed method shows a very good quality of restoration on this type of image, particularly when the percentage of noise is high. The MLVMF provides a high PSNR value of 5.5% and a low NCD value of 18.2%. Finally, an optimized Field-Programmable Gate Array (FPGA) design is proposed to implement the proposed method for real-time processing. The proposed hardware implementation allows an execution time equal to 9 ms per 256 × 256 color image.
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spelling pubmed-96892772022-11-25 New Real-Time Impulse Noise Removal Method Applied to Chest X-ray Images Rashid, Nasr Berriri, Kamel Albekairi, Mohammed Kaaniche, Khaled Ben Atitallah, Ahmed Khan, Muhammad Attique El-Hamrawy, Osama I. Diagnostics (Basel) Article In this paper, we propose a new Modified Laplacian Vector Median Filter (MLVMF) for real-time denoising complex images corrupted by “salt and pepper” impulsive noise. The method consists of two rounds with three steps each: the first round starts with the identification of pixels that may be contaminated by noise using a Modified Laplacian Filter. Then, corrupted pixels pass a neighborhood-based validation test. Finally, the Vector Median Filter is used to replace noisy pixels. The MLVMF uses a 5 × 5 window to observe the intensity variations around each pixel of the image with a rotation step of π/8 while the classic Laplacian filters often use rotation steps of π/2 or π/4. We see better identification of noise-corrupted pixels thanks to this rotation step refinement. Despite this advantage, a high percentage of the impulsive noise may cause two or more corrupted pixels (with the same intensity) to collide, preventing the identification of noise-corrupted pixels. A second round is then necessary using a second set of filters, still based on the Laplacian operator, but allowing focusing only on the collision phenomenon. To validate our method, MLVMF is firstly tested on standard images, with a noise percentage varying from 3% to 30%. Obtained performances in terms of processing time, as well as image restoration quality through the PSNR (Peak Signal to Noise Ratio) and the NCD (Normalized Color Difference) metrics, are compared to the performances of VMF (Vector Median Filter), VMRHF (Vector Median-Rational Hybrid Filter), and MSMF (Modified Switching Median Filter). A second test is performed on several noisy chest x-ray images used in cardiovascular disease diagnosis as well as COVID-19 diagnosis. The proposed method shows a very good quality of restoration on this type of image, particularly when the percentage of noise is high. The MLVMF provides a high PSNR value of 5.5% and a low NCD value of 18.2%. Finally, an optimized Field-Programmable Gate Array (FPGA) design is proposed to implement the proposed method for real-time processing. The proposed hardware implementation allows an execution time equal to 9 ms per 256 × 256 color image. MDPI 2022-11-09 /pmc/articles/PMC9689277/ /pubmed/36359581 http://dx.doi.org/10.3390/diagnostics12112738 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rashid, Nasr
Berriri, Kamel
Albekairi, Mohammed
Kaaniche, Khaled
Ben Atitallah, Ahmed
Khan, Muhammad Attique
El-Hamrawy, Osama I.
New Real-Time Impulse Noise Removal Method Applied to Chest X-ray Images
title New Real-Time Impulse Noise Removal Method Applied to Chest X-ray Images
title_full New Real-Time Impulse Noise Removal Method Applied to Chest X-ray Images
title_fullStr New Real-Time Impulse Noise Removal Method Applied to Chest X-ray Images
title_full_unstemmed New Real-Time Impulse Noise Removal Method Applied to Chest X-ray Images
title_short New Real-Time Impulse Noise Removal Method Applied to Chest X-ray Images
title_sort new real-time impulse noise removal method applied to chest x-ray images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689277/
https://www.ncbi.nlm.nih.gov/pubmed/36359581
http://dx.doi.org/10.3390/diagnostics12112738
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