Year
Month
(Peer-Reviewed) Unsupervised learning enabled label-free single-pixel imaging for resilient information transmission through unknown dynamic scattering media
Fujie Li 李甫杰 ¹, Haoyu Zhang 张昊宇 ¹, Zhilan Lu 卢芝蓝 ¹, Li Yao 姚力 ¹, Yuan Wei 魏圆 ¹, Ziwei Li 李子薇 ¹, Feng Bao 鲍峰 ¹, Junwen Zhang 张俊文 ¹, Yingjun Zhou 周盈君 ¹, Nan Chi 迟楠 ¹ ²
¹ Key Laboratory for the Information Science of Electromagnetic Waves (MoE), Department of Communication Science and Engineering, Fudan University, Shanghai 200433, China
中国 上海 复旦大学电磁波信息科学教育部重点实验室
² Shanghai Engineering Research Center of Low-Earth-Orbit Satellite Communication and Applications, and Shanghai Collaborative Innovation Center of Low-Earth-Orbit Satellite Communication Technology, Shanghai 200433, China
中国 上海 上海低轨卫星通信与应用工程技术研究中心 上海市低轨卫星通信技术协同创新中心
Opto-Electronic Advances, 2025-10-25
Abstract

Single-pixel imaging (SPI) is a prominent scattering media imaging technique that allows image transmission via one-dimensional detection under structured illumination, with applications spanning from long-range imaging to microscopy. Recent advancements leveraging deep learning (DL) have significantly improved SPI performance, especially at low compression ratios. However, most DL-based SPI methods proposed so far rely heavily on extensive labeled datasets for supervised training, which are often impractical in real-world scenarios.

Here, we propose an unsupervised learning-enabled label-free SPI method for resilient information transmission through unknown dynamic scattering media. Additionally, we introduce a physics-informed autoencoder framework to optimize encoding schemes, further enhancing image quality at low compression ratios. Simulation and experimental results demonstrate that high-efficiency data transmission with structural similarity exceeding 0.9 is achieved through challenging turbulent channels.

Moreover, experiments demonstrate that in a 5 m underwater dynamic turbulent channel, USAF target imaging quality surpasses traditional methods by over 13 dB. The compressive encoded transmission of 720×720 resolution video exceeding 30 seconds with great fidelity is also successfully demonstrated. These preliminary results suggest that our proposed method opens up a new paradigm for resilient information transmission through unknown dynamic scattering media and holds potential for broader applications within many other scattering media imaging technologies.
Unsupervised learning enabled label-free single-pixel imaging for resilient information transmission through unknown dynamic scattering media_1
Unsupervised learning enabled label-free single-pixel imaging for resilient information transmission through unknown dynamic scattering media_2
Unsupervised learning enabled label-free single-pixel imaging for resilient information transmission through unknown dynamic scattering media_3
Unsupervised learning enabled label-free single-pixel imaging for resilient information transmission through unknown dynamic scattering media_4
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