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Enhancement of various images using coefficients obtained from a class of Sakaguchi type functions

Digital image processing has a wide range of uses, including robotics and automated inspection of industrial parts. Other uses include remote sensing using satellites and other spacecraft, image transmission and storage for business applications, medical processing, and Acoustic image processing. Th...

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Detalles Bibliográficos
Autores principales: Aarthy, B., Keerthi, B. Srutha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10618230/
https://www.ncbi.nlm.nih.gov/pubmed/37907695
http://dx.doi.org/10.1038/s41598-023-45938-y
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author Aarthy, B.
Keerthi, B. Srutha
author_facet Aarthy, B.
Keerthi, B. Srutha
author_sort Aarthy, B.
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description Digital image processing has a wide range of uses, including robotics and automated inspection of industrial parts. Other uses include remote sensing using satellites and other spacecraft, image transmission and storage for business applications, medical processing, and Acoustic image processing. The process of highlighting particular intriguing features in a hidden image is known as image enhancement. We can accomplish this by altering the brightness, contrast, etc. The generated output is more suitable than the original image for some particular purposes. The proposed algorithm which is based on the convolution of coefficient bounds of a subclass [Formula: see text] obtained using Mittag-Leffler type Poisson Distribution is tested on three image data sets with different dimensions and image formats (PNG, JPEG, TIFF, etc.) and its PSNR, SSIM, MSE, RMSE, PCC and MAE values are observed to check the quality of the enhanced images.
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spelling pubmed-106182302023-11-02 Enhancement of various images using coefficients obtained from a class of Sakaguchi type functions Aarthy, B. Keerthi, B. Srutha Sci Rep Article Digital image processing has a wide range of uses, including robotics and automated inspection of industrial parts. Other uses include remote sensing using satellites and other spacecraft, image transmission and storage for business applications, medical processing, and Acoustic image processing. The process of highlighting particular intriguing features in a hidden image is known as image enhancement. We can accomplish this by altering the brightness, contrast, etc. The generated output is more suitable than the original image for some particular purposes. The proposed algorithm which is based on the convolution of coefficient bounds of a subclass [Formula: see text] obtained using Mittag-Leffler type Poisson Distribution is tested on three image data sets with different dimensions and image formats (PNG, JPEG, TIFF, etc.) and its PSNR, SSIM, MSE, RMSE, PCC and MAE values are observed to check the quality of the enhanced images. Nature Publishing Group UK 2023-10-31 /pmc/articles/PMC10618230/ /pubmed/37907695 http://dx.doi.org/10.1038/s41598-023-45938-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Aarthy, B.
Keerthi, B. Srutha
Enhancement of various images using coefficients obtained from a class of Sakaguchi type functions
title Enhancement of various images using coefficients obtained from a class of Sakaguchi type functions
title_full Enhancement of various images using coefficients obtained from a class of Sakaguchi type functions
title_fullStr Enhancement of various images using coefficients obtained from a class of Sakaguchi type functions
title_full_unstemmed Enhancement of various images using coefficients obtained from a class of Sakaguchi type functions
title_short Enhancement of various images using coefficients obtained from a class of Sakaguchi type functions
title_sort enhancement of various images using coefficients obtained from a class of sakaguchi type functions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10618230/
https://www.ncbi.nlm.nih.gov/pubmed/37907695
http://dx.doi.org/10.1038/s41598-023-45938-y
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