Bibliometrix research of noise removal techniques in digital images for defense
In modern defense applications, the accuracy and clarity of digital images are crucial, especially for tasks like surveillance, reconnaissance, and intelligence gathering. However, noise introduced during image acquisition or transmission significantly degrades image quality. This paper presents a c...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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FoundAE
2025-04-01
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| Series: | International Journal of Applied Mathematics, Sciences, and Technology for National Defense |
| Subjects: | |
| Online Access: | https://journal.foundae.com/index.php/JAS-ND/article/view/463 |
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| _version_ | 1850187615386468352 |
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| author | Fulkan Kafilah Al Husein Muhammad Yusuf Al Habsy Damaris Nugrahita Christi Agnes Emanuela Hutagaol Ahmad Kadri bin Junoh |
| author_facet | Fulkan Kafilah Al Husein Muhammad Yusuf Al Habsy Damaris Nugrahita Christi Agnes Emanuela Hutagaol Ahmad Kadri bin Junoh |
| author_sort | Fulkan Kafilah Al Husein |
| collection | DOAJ |
| description | In modern defense applications, the accuracy and clarity of digital images are crucial, especially for tasks like surveillance, reconnaissance, and intelligence gathering. However, noise introduced during image acquisition or transmission significantly degrades image quality. This paper presents a comprehensive review of various noise removal techniques employed in digital image processing for defense systems. The review focuses on both linear and non-linear methods, including matrix decomposition, hybrid deep learning, Generative Adversarial Networks (GANs), and trimming filters. Emphasis is placed on the effectiveness of each technique in enhancing image quality while preserving critical details. The use of linear and non-linear methods such as deep learning-based approaches is shown to outperform traditional linear filters in handling complex noise patterns, particularly in scenarios requiring precise object detection and image restoration. The paper highlights a comprehensive overview of the researched literature and shows the latest trends and developments in the field. Finally, recommendations for future research and the development of more robust noise reduction methods are provided, aiming to improve operational effectiveness in defense applications. |
| format | Article |
| id | doaj-art-5f799c2b78a64fef8fb6f81fec82d8b0 |
| institution | OA Journals |
| issn | 2986-0776 2985-9352 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | FoundAE |
| record_format | Article |
| series | International Journal of Applied Mathematics, Sciences, and Technology for National Defense |
| spelling | doaj-art-5f799c2b78a64fef8fb6f81fec82d8b02025-08-20T02:16:03ZengFoundAEInternational Journal of Applied Mathematics, Sciences, and Technology for National Defense2986-07762985-93522025-04-013192410.58524/app.sci.def.v3i1.463273Bibliometrix research of noise removal techniques in digital images for defenseFulkan Kafilah Al Husein0Muhammad Yusuf Al Habsy1Damaris Nugrahita Christi2Agnes Emanuela Hutagaol3Ahmad Kadri bin Junoh4Indonesia Defense UniversityIndonesia Defense UniversityIndonesia Defense UniversityIndonesia Defense UniversityUniversiti Malaysia PerlisIn modern defense applications, the accuracy and clarity of digital images are crucial, especially for tasks like surveillance, reconnaissance, and intelligence gathering. However, noise introduced during image acquisition or transmission significantly degrades image quality. This paper presents a comprehensive review of various noise removal techniques employed in digital image processing for defense systems. The review focuses on both linear and non-linear methods, including matrix decomposition, hybrid deep learning, Generative Adversarial Networks (GANs), and trimming filters. Emphasis is placed on the effectiveness of each technique in enhancing image quality while preserving critical details. The use of linear and non-linear methods such as deep learning-based approaches is shown to outperform traditional linear filters in handling complex noise patterns, particularly in scenarios requiring precise object detection and image restoration. The paper highlights a comprehensive overview of the researched literature and shows the latest trends and developments in the field. Finally, recommendations for future research and the development of more robust noise reduction methods are provided, aiming to improve operational effectiveness in defense applications.https://journal.foundae.com/index.php/JAS-ND/article/view/463median filtersmean filterssalt and pepper noiseimpulse noiseimage restoration |
| spellingShingle | Fulkan Kafilah Al Husein Muhammad Yusuf Al Habsy Damaris Nugrahita Christi Agnes Emanuela Hutagaol Ahmad Kadri bin Junoh Bibliometrix research of noise removal techniques in digital images for defense International Journal of Applied Mathematics, Sciences, and Technology for National Defense median filters mean filters salt and pepper noise impulse noise image restoration |
| title | Bibliometrix research of noise removal techniques in digital images for defense |
| title_full | Bibliometrix research of noise removal techniques in digital images for defense |
| title_fullStr | Bibliometrix research of noise removal techniques in digital images for defense |
| title_full_unstemmed | Bibliometrix research of noise removal techniques in digital images for defense |
| title_short | Bibliometrix research of noise removal techniques in digital images for defense |
| title_sort | bibliometrix research of noise removal techniques in digital images for defense |
| topic | median filters mean filters salt and pepper noise impulse noise image restoration |
| url | https://journal.foundae.com/index.php/JAS-ND/article/view/463 |
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