Photon-level single-pixel wavefront imaging through turbid underwater environment
Fanjin Zeng, Yaoxing Bian, Kai Song, Hongrui Liu, Shijun Zhao, Xingyu Wang, Fuyi Zhang, Hongda Ge, Dong Wang, Liantuan Xiao
Abstract
Single-pixel wavefront imaging provides the possibility to accurately measure and process complex wavefronts in extremely low-light scenes. However, the noises introduced in the turbid environment greatly affect the quality of wavefront imaging. Here, we propose a highly robust single-pixel wavefront detection technology with phase-denoising neural network. Aiming at different levels of noise in various turbid underwater environments, the proposed technology demonstrates adaptive denoising capabilities and can actively adjust to variations in underwater environments. Based on the advantages of single-photon detection technology, the wavefront images with arbitrary orbital angular momentum modes can be reconstructed with only 0.022 photon per pattern per pixel. Meanwhile, the results demonstrate that the proposed technology can effectively reduce noises in underwater environments with turbidity levels ranging from 0.1 to 100 NTU. The presented technology promotes the practical application of single-pixel wavefront imaging systems in the underwater visible light communication.