A Dual-Path Computational Ghost Imaging Method Based on Convolutional Neural Networks
Hexiao Wang, Jianan Wu, Mingcong Wang, Yu Xia · 2024
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Description
Wang, Wu, Wang, and Xia present a study from twenty twenty-four on a wider way to make pictures with light. Ghost imaging builds a picture from light patterns, not from a direct view of the object. It resists noise well, but its view range has stayed narrow. The team adds a second light path so the system can gather facts from a wider area. They feed both paths into a smart network that rebuilds the target picture.
The network also has a focus step that shifts weight to the most useful signals. Tests in simulation show the method works and rebuilds pictures well. The authors say the wider range makes ghost imaging more useful in real settings. It offers a fresh path for later imaging tools.
Catalog record
| CREATOR | Hexiao Wang, Jianan Wu, Mingcong Wang, Yu Xia |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 23 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |