Karim, Faten Khalid and Jalab, Hamid A. and Ibrahim, Rabha W. and Al-Shamasneh, Ala'a R. (2022) Mathematical model based on fractional trace operator for COVID-19 image enhancement. Journal of King Saud University Science, 34 (7). ISSN 1018-3647, DOI https://doi.org/10.1016/j.jksus.2022.102254.
Full text not available from this repository.Abstract
The medical image enhancement is major class in the image processing which aims for improving the medical diagnosis results. The improving of the quality of the captured medical images is considered as a challenging task in medical image. In this study, a trace operator in fractional calculus linked with the derivative of fractional Renyi entropy is proposed to enhance the low contrast COVID-19 images. The pixel probability values of the input image are obtained first in the proposed image enhancement model. Then the covariance matrix between the input image and the probability of a pixel intensity of the input image to be calculated. Finally, the image enhancement is performed by using the convolution of covariance matrix result with the input image. The proposed enhanced image algorithm is tested against three medical image datasets with different qualities. The experimental results show that the proposed medical image enhancement algorithm achieves the good image quality assessments using both the BRISQUE, and PIQE quality measures. Moreover, the experimental results indicated that the final enhancement of medical images using the proposed algorithm has outperformed other methods. Overall, the proposed algorithm has significantly improved the image which can be useful for medical diagnosis process. (C) 2022 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Item Type: | Article |
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Funders: | Princess Nourah bint Abdulrahman University [PNURSP2022R300] |
Uncontrolled Keywords: | Fractional calculus; Trace operator; Fractional Renyi entropy; COVI-19 images; Image enhancement |
Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Computer Science & Information Technology |
Depositing User: | Ms. Juhaida Abd Rahim |
Date Deposited: | 25 Aug 2023 06:49 |
Last Modified: | 25 Aug 2023 06:49 |
URI: | http://eprints.um.edu.my/id/eprint/40927 |
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