Photon-level single-pixel 3D tomography with masked attention network

• DOI: 10.1364/oe.510706
• Publication Date: 2024-01-15T09:00:09Z
• Authors: Kai Song; Yaoxing Bian; Fanjin Zeng; Zhe Liu; Shuangping Han; Jiamin Li; Jiazhao Tian; Kangze Li; Xiaoyu Shi; Liantuan Xiao
• Keywords: 02 engineering and technology; 0210 nano-technology

Tomography plays an important role in characterizing the three-dimensional structure of samples within specialized scenarios. In the paper, a masked attention network is presented to eliminate interference from different layers of the sample, substantially enhancing the resolution for photon-level single-pixel tomographic imaging. The simulation and experimental results have demonstrated that the axial resolution and lateral resolution of the imaging system can be improved by about 3 and 2 times respectively, with a sampling rate of 3.0 %. The scheme is expected to be seamlessly integrated into various tomography systems, which is conducive to promoting the tomographic imaging for biology, medicine, and materials science.