Super-resolution in disordered media using neural networks
Fuente:
arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
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| _version_ | 1866929614476017664 |
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| author | Christie, Alexander Leibovich, Matan Moscoso, Miguel Novikov, Alexei Papanicolaou, George Tsogka, Chrysoula |
| author_facet | Christie, Alexander Leibovich, Matan Moscoso, Miguel Novikov, Alexei Papanicolaou, George Tsogka, Chrysoula |
| contents | We propose a methodology that exploits large and diverse data sets to accurately estimate the ambient medium's Green's functions in strongly scattering media. Given these estimates, obtained with and without the use of neural networks, excellent imaging results are achieved, with a resolution that is better than that of a homogeneous medium. This phenomenon, also known as super-resolution, occurs because the ambient scattering medium effectively enhances the physical imaging aperture. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_21556 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Super-resolution in disordered media using neural networks Christie, Alexander Leibovich, Matan Moscoso, Miguel Novikov, Alexei Papanicolaou, George Tsogka, Chrysoula Machine Learning Computer Vision and Pattern Recognition Image and Video Processing We propose a methodology that exploits large and diverse data sets to accurately estimate the ambient medium's Green's functions in strongly scattering media. Given these estimates, obtained with and without the use of neural networks, excellent imaging results are achieved, with a resolution that is better than that of a homogeneous medium. This phenomenon, also known as super-resolution, occurs because the ambient scattering medium effectively enhances the physical imaging aperture. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. |
| title | Super-resolution in disordered media using neural networks |
| topic | Machine Learning Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2410.21556 |