Recent Advancements in Microscopy Image Enhancement using Deep Learning: A Survey
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866908560255877120 |
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| author | Dutta, Debasish Sonowal, Neeharika Barauh, Risheraj Chetia, Deepjyoti Kalita, Sanjib Kr |
| author_facet | Dutta, Debasish Sonowal, Neeharika Barauh, Risheraj Chetia, Deepjyoti Kalita, Sanjib Kr |
| contents | Microscopy image enhancement plays a pivotal role in understanding the details of biological cells and materials at microscopic scales. In recent years, there has been a significant rise in the advancement of microscopy image enhancement, specifically with the help of deep learning methods. This survey paper aims to provide a snapshot of this rapidly growing state-of-the-art method, focusing on its evolution, applications, challenges, and future directions. The core discussions take place around the key domains of microscopy image enhancement of super-resolution, reconstruction, and denoising, with each domain explored in terms of its current trends and their practical utility of deep learning. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2509_15363 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Recent Advancements in Microscopy Image Enhancement using Deep Learning: A Survey Dutta, Debasish Sonowal, Neeharika Barauh, Risheraj Chetia, Deepjyoti Kalita, Sanjib Kr Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning Microscopy image enhancement plays a pivotal role in understanding the details of biological cells and materials at microscopic scales. In recent years, there has been a significant rise in the advancement of microscopy image enhancement, specifically with the help of deep learning methods. This survey paper aims to provide a snapshot of this rapidly growing state-of-the-art method, focusing on its evolution, applications, challenges, and future directions. The core discussions take place around the key domains of microscopy image enhancement of super-resolution, reconstruction, and denoising, with each domain explored in terms of its current trends and their practical utility of deep learning. |
| title | Recent Advancements in Microscopy Image Enhancement using Deep Learning: A Survey |
| topic | Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2509.15363 |