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A Novel Image Processing Approach to Enhancement and Compression of X-ray Images
At present, there is an increase in the capacity of data generated and stored in the medical area. Thus, for the efficient handling of these extensive data, the compression methods need to be re-explored by considering the algorithm’s complexity. To reduce the redundancy of the contents of the image...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8297375/ https://www.ncbi.nlm.nih.gov/pubmed/34206486 http://dx.doi.org/10.3390/ijerph18136724 |
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author | Pourasad, Yaghoub Cavallaro, Fausto |
author_facet | Pourasad, Yaghoub Cavallaro, Fausto |
author_sort | Pourasad, Yaghoub |
collection | PubMed |
description | At present, there is an increase in the capacity of data generated and stored in the medical area. Thus, for the efficient handling of these extensive data, the compression methods need to be re-explored by considering the algorithm’s complexity. To reduce the redundancy of the contents of the image, thus increasing the ability to store or transfer information in optimal form, an image processing approach needs to be considered. So, in this study, two compression techniques, namely lossless compression and lossy compression, were applied for image compression, which preserves the image quality. Moreover, some enhancing techniques to increase the quality of a compressed image were employed. These methods were investigated, and several comparison results are demonstrated. Finally, the performance metrics were extracted and analyzed based on state-of-the-art methods. PSNR, MSE, and SSIM are three performance metrics that were used for the sample medical images. Detailed analysis of the measurement metrics demonstrates better efficiency than the other image processing techniques. This study helps to better understand these strategies and assists researchers in selecting a more appropriate technique for a given use case. |
format | Online Article Text |
id | pubmed-8297375 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82973752021-07-23 A Novel Image Processing Approach to Enhancement and Compression of X-ray Images Pourasad, Yaghoub Cavallaro, Fausto Int J Environ Res Public Health Article At present, there is an increase in the capacity of data generated and stored in the medical area. Thus, for the efficient handling of these extensive data, the compression methods need to be re-explored by considering the algorithm’s complexity. To reduce the redundancy of the contents of the image, thus increasing the ability to store or transfer information in optimal form, an image processing approach needs to be considered. So, in this study, two compression techniques, namely lossless compression and lossy compression, were applied for image compression, which preserves the image quality. Moreover, some enhancing techniques to increase the quality of a compressed image were employed. These methods were investigated, and several comparison results are demonstrated. Finally, the performance metrics were extracted and analyzed based on state-of-the-art methods. PSNR, MSE, and SSIM are three performance metrics that were used for the sample medical images. Detailed analysis of the measurement metrics demonstrates better efficiency than the other image processing techniques. This study helps to better understand these strategies and assists researchers in selecting a more appropriate technique for a given use case. MDPI 2021-06-22 /pmc/articles/PMC8297375/ /pubmed/34206486 http://dx.doi.org/10.3390/ijerph18136724 Text en © 2021 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 Pourasad, Yaghoub Cavallaro, Fausto A Novel Image Processing Approach to Enhancement and Compression of X-ray Images |
title | A Novel Image Processing Approach to Enhancement and Compression of X-ray Images |
title_full | A Novel Image Processing Approach to Enhancement and Compression of X-ray Images |
title_fullStr | A Novel Image Processing Approach to Enhancement and Compression of X-ray Images |
title_full_unstemmed | A Novel Image Processing Approach to Enhancement and Compression of X-ray Images |
title_short | A Novel Image Processing Approach to Enhancement and Compression of X-ray Images |
title_sort | novel image processing approach to enhancement and compression of x-ray images |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8297375/ https://www.ncbi.nlm.nih.gov/pubmed/34206486 http://dx.doi.org/10.3390/ijerph18136724 |
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