This paper demonstrates mid-infrared (MIR) single-photon computational imaging using a single-element silicon detector. The method employs nonlinear structured detection with encoded time-varying pump patterns imprinted onto the MIR object image via sum-frequency generation. This translates the MIR radiation into the visible region, enabling single-photon upconversion detection. Compressed sensing and deep learning algorithms reconstruct MIR images under sub-Nyquist sampling and low-light conditions. The system achieves single-pixel simplicity, single-photon sensitivity, and room-temperature operation, opening new avenues for sensitive imaging at longer infrared wavelengths or terahertz frequencies.
Publisher
Nature Communications
Published On
Feb 25, 2023
Authors
Yinqi Wang, Kun Huang, Jianan Fang, Ming Yan, E Wu, Heping Zeng
Tags
mid-infrared imaging
single-photon detection
compressed sensing
deep learning
room-temperature operation
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