Mid-infrared single-pixel imaging at the single-photon level

Single-pixel cameras have recently emerged as promising alternatives to multi-pixel sensors due to reduced costs and superior durability, which are particularly attractive for mid-infrared (MIR) imaging pertinent to applications including industry inspection and biomedical diagnosis. To date, MIR single-pixel photon-sparse imaging has yet been realized, which urgently calls for high-sensitivity optical detectors and high-fidelity spatial modulators. Here, we demonstrate a MIR single-photon computational imaging with a single-element silicon detector. The underlying methodology relies on nonlinear structured detection, where encoded time-varying pump patterns are optically imprinted onto a MIR object image through sum-frequency generation. Simultaneously, the MIR radiation is spectrally translated into the visible region, thus permitting infrared single-photon upconversion detection. Then, the use of advanced algorithms of compressed sensing and deep learning allows us to reconstruct MIR images under sub-Nyquist sampling and photon-starving illumination. The presented paradigm of single-pixel upconversion imaging is featured with single-pixel simplicity, single-photon sensitivity, and room-temperature operation, which would establish a new path for sensitive imaging at longer infrared wavelengths or terahertz frequencies, where high-sensitivity photon counters and high-fidelity spatial modulators are typically hard to access. The authors present an implementation of mid-infrared single-photon computational imaging with a single-element silicon detector. In addition to unique features of single-pixel simplicity and room-temperature operation, the infrared imager offers a superior sensitivity at the single-photon level.

Automated summary

Single-pixel cameras offer a promising alternative to multi-pixel sensors for mid-infrared (MIR) imaging. In this study, a MIR single-photon computational imaging method with a single-element silicon detector is demonstrated, employing nonlinear structured detection and upconversion detection. Advanced algorithms enable MIR image reconstruction under sub-Nyquist sampling and photon-starving illumination. This single-pixel upconversion imaging paradigm provides simplicity, single-photon sensitivity, and room-temperature operation, opening up new possibilities for sensitive imaging at longer infrared wavelengths or terahertz frequencies.