The sensitivity of optical spectrum analysis plays a crucial role in fields such as remote sensing, astronomical observation, Raman spectroscopy, and fluorescence spectroscopy. Photon-counting spectrometers based on single-photon detectors have been demonstrated as highly sensitive tools for optical spectrum analysis and are now widely used in these areas. In addition, single-photon detectors can record the arrival times of photons, enabling photon-counting spectrometers to acquire not only spectral information but also information in additional dimensions, such as scene depth or fluorescence lifetime. This makes high-dimensional imaging possible.

However, due to the challenges in developing arrayed single-photon detectors, high-dimensional imaging based on photon-counting spectrometers often requires scanning across spatial or spectral dimensions. This limits imaging speed and practical applications. To accelerate the imaging process, we propose an imaging scheme that applies compressed sensing across both spectral and spatial dimensions. It is named Photon-Counting Compressed Spatial-Spectral imaging (PCCSSI). PCCSSI combines single-pixel imaging, time-of-flight (ToF) measurement and compressed-sensing-based spectrum reconstruction. We further performed proof-of-principle experiments using a photon-counting spectrometer based on metasurfaces and superconducting nanowire single-photon detectors (SNSPDs).

Under photon-sparse scenarios with a photon-counting rate of about 123 kHz, PCCSSI successfully demonstrated spatial–spectral high-dimensional imaging of multiple objects with distinct spectral signatures located at different positions. The measurement time can be reduced to a few minutes, achieving an acceleration of several orders of magnitude compared with previous works. This work provides a highly promising way for high-dimensional imaging under photon-sparse scenarios, such as spectral LiDAR, Raman spectral imaging and spectral fluorescence lifetime imaging.

This work was published in Laser & Photonics Reviews (https://onlinelibrary.wiley.com/doi/10.1002/lpor.202500618) at 18 August 2025 with the title of "Photon-Counting Compressed Spatial-Spectral Imaging for 4D Information Retrieval". Ph.D. candidates Mingzhong Hu and Jingyuan Zheng are the first authors of this paper. Prof. Wei Zhang is the corresponding author.