Isil, Ç;
Gan, T;
Ardic, FO;
Mentesoglu, K;
Digani, J;
Karaca, H;
Chen, H;
... Ozcan, A; + view all
(2024)
Image denoising using diffractive optical processors.
In:
Proceedings CLEO 2024: Part of Conference on Lasers & Electro-Optics.
Optica Publishing Group
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cleo_fs-2024-ftu3g.2.pdf - Accepted Version Access restricted to UCL open access staff until 11 May 2025. Download (3MB) |
Abstract
We report an image denoising analog processor composed of passive diffractive layers engineered through deep learning to filter out various types of noise from input images, instantly projecting denoised images at the output field-of-view.
| Type: | Proceedings paper |
|---|---|
| Title: | Image denoising using diffractive optical processors |
| Event: | CLEO: Fundamental Science 2024 |
| Dates: | 2024 |
| DOI: | 10.1364/CLEO_FS.2024.FTu3G.2 |
| Publisher version: | http://dx.doi.org/10.1364/cleo_fs.2024.ftu3g.2 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10201177 |
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