Digital Image Progressive Fusion Method Based on Discrete Cosine Transform
The current progressive fusion methods for digital images have poor denoising performance, which leads to a decrease in image quality after progressive fusion. Therefore, a new method for digital image progressive fusion was proposed based on discrete cosine transform, and its effectiveness was veri...
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Format: | Article |
Language: | English |
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Wiley
2023-01-01
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Series: | Journal of Mathematics |
Online Access: | http://dx.doi.org/10.1155/2023/9905604 |
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author | Jiezi Chen |
author_facet | Jiezi Chen |
author_sort | Jiezi Chen |
collection | DOAJ |
description | The current progressive fusion methods for digital images have poor denoising performance, which leads to a decrease in image quality after progressive fusion. Therefore, a new method for digital image progressive fusion was proposed based on discrete cosine transform, and its effectiveness was verified through experiments. The experimental results show that the proposed method has a PSNR value higher than 42.13 db in image fusion, both of which are higher than the comparison method, and the fusion effect comparison also has higher image quality. In terms of fusion time, the time of the research method is lower than that of the comparison method when the data volume is between 10 and 100, while in the comparison of structural similarity, the structural similarity of the image fused by the research method is always higher than 0.83. Overall, the fusion method proposed in the study results in higher image quality and is effective in progressive digital image fusion, which is of great significance for practical digital image fusion. |
format | Article |
id | doaj-art-aa4986646b554c818933100d0bde7272 |
institution | Kabale University |
issn | 2314-4785 |
language | English |
publishDate | 2023-01-01 |
publisher | Wiley |
record_format | Article |
series | Journal of Mathematics |
spelling | doaj-art-aa4986646b554c818933100d0bde72722025-02-03T06:48:31ZengWileyJournal of Mathematics2314-47852023-01-01202310.1155/2023/9905604Digital Image Progressive Fusion Method Based on Discrete Cosine TransformJiezi Chen0Digital Art AcademyThe current progressive fusion methods for digital images have poor denoising performance, which leads to a decrease in image quality after progressive fusion. Therefore, a new method for digital image progressive fusion was proposed based on discrete cosine transform, and its effectiveness was verified through experiments. The experimental results show that the proposed method has a PSNR value higher than 42.13 db in image fusion, both of which are higher than the comparison method, and the fusion effect comparison also has higher image quality. In terms of fusion time, the time of the research method is lower than that of the comparison method when the data volume is between 10 and 100, while in the comparison of structural similarity, the structural similarity of the image fused by the research method is always higher than 0.83. Overall, the fusion method proposed in the study results in higher image quality and is effective in progressive digital image fusion, which is of great significance for practical digital image fusion.http://dx.doi.org/10.1155/2023/9905604 |
spellingShingle | Jiezi Chen Digital Image Progressive Fusion Method Based on Discrete Cosine Transform Journal of Mathematics |
title | Digital Image Progressive Fusion Method Based on Discrete Cosine Transform |
title_full | Digital Image Progressive Fusion Method Based on Discrete Cosine Transform |
title_fullStr | Digital Image Progressive Fusion Method Based on Discrete Cosine Transform |
title_full_unstemmed | Digital Image Progressive Fusion Method Based on Discrete Cosine Transform |
title_short | Digital Image Progressive Fusion Method Based on Discrete Cosine Transform |
title_sort | digital image progressive fusion method based on discrete cosine transform |
url | http://dx.doi.org/10.1155/2023/9905604 |
work_keys_str_mv | AT jiezichen digitalimageprogressivefusionmethodbasedondiscretecosinetransform |