Gespeichert in:
| Hauptverfasser: | , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2403.04240 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866914706308988928 |
|---|---|
| author | Zheng, Pengcheng Zhang, Songqian Ma, Zhu Niu, Haipo Wu, Jiatao Huang, Zerui Han, Chengyin Lu, Bo Liu, Peiliang Lee, Chaohong |
| author_facet | Zheng, Pengcheng Zhang, Songqian Ma, Zhu Niu, Haipo Wu, Jiatao Huang, Zerui Han, Chengyin Lu, Bo Liu, Peiliang Lee, Chaohong |
| contents | The noise in absorption imaging of cold atoms significantly impacts measurement accuracy across a range of applications with ultracold atoms. It is crucial to adopt an approach that offers effective denoising capabilities without compromising the unique structure of the atoms. Here we introduce a novel image enhancement algorithm for cold atomic absorption imaging. The algorithm successfully suppresses background noise, enhancing image contrast significantly. Experimental results showcase that this approach can enhance the accuracy of cold atom particle number measurements by approximately tenfold, all while preserving essential information. Moreover, the method exhibits exceptional performance and robustness when confronted with fringe noise and multi-component imaging scenarios, offering high stability. Importantly, the optimization process is entirely automated, eliminating the need for manual parameter selection. The method is both compatible and practical, making it applicable across various absorption imaging fields. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_04240 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Image enhancement algorithm for absorption imaging Zheng, Pengcheng Zhang, Songqian Ma, Zhu Niu, Haipo Wu, Jiatao Huang, Zerui Han, Chengyin Lu, Bo Liu, Peiliang Lee, Chaohong Quantum Physics The noise in absorption imaging of cold atoms significantly impacts measurement accuracy across a range of applications with ultracold atoms. It is crucial to adopt an approach that offers effective denoising capabilities without compromising the unique structure of the atoms. Here we introduce a novel image enhancement algorithm for cold atomic absorption imaging. The algorithm successfully suppresses background noise, enhancing image contrast significantly. Experimental results showcase that this approach can enhance the accuracy of cold atom particle number measurements by approximately tenfold, all while preserving essential information. Moreover, the method exhibits exceptional performance and robustness when confronted with fringe noise and multi-component imaging scenarios, offering high stability. Importantly, the optimization process is entirely automated, eliminating the need for manual parameter selection. The method is both compatible and practical, making it applicable across various absorption imaging fields. |
| title | Image enhancement algorithm for absorption imaging |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2403.04240 |