Noise-Resilient Ptychographic Imaging with Deep Learning
We develop Ptyde-Net for enhancing the SNR in ptychographic phase retrieval in noisy environments, with specially designed denoising modules and attention mechanisms, which are evidenced by remarkable improvements in both PSNR and SSIM. © 2024 The Author(s)
Authors
- Jun Cheng (ORCID: https://orcid.org/0000-0003-1786-6188)
- Han Yue (ORCID: https://orcid.org/0000-0002-8888-2727)
- Yu‐Xuan Ren (ORCID: https://orcid.org/0000-0002-4641-3148)
- Feng Shu
- Yun Xie
- Xin Lou
Institutions
- Agency for Science, Technology and Research (SG)
- Fudan University (CN)
- Institute for Infocomm Research (SG)
- ShanghaiTech University (CN)
Publication Details
- Published
- 2024-08-04
- DOI
- https://doi.org/10.1109/cleo-pr60912.2024.10676456
- Citations
- 1
- Primary Topic
- Advanced X-ray Imaging Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.61