Infrared Single-Pixel Hyperspectral Imaging via Spatial-Temporal Multiplexing

Abstract

Near-infrared (NIR) hyperspectral imaging is widely used to reveal morphological and chemical information. However, conventional spectral imagers usually rely on costly focal plane arrays and suffer from data redundancy and inefficiencies in spatial-spectral data acquisition. Here, we devise and implement a single-pixel NIR hyperspectral imaging system based on high-fidelity spectrum-to-time mapping and high-precision spatial-encoding compressive measurements. The system employs a single-mode telecommunication fiber for temporal dispersion and a programmable spatial light modulator to impose structured spatial patterns, with all signals detected by a single InGaAs photodetector. By correlating temporally stretched waveforms with spatial encodings, we reconstruct 64$\times$64 spatially resolved hyperspectral datacubes spanning 50 spectral bands over the 1550-1600 nm range. Furthermore, real-time monitoring of dynamic liquid injection is demonstrated at a datacube refreshing rate of 12 Hz under sub-Nyquist sampling. The presented architecture features single-pixel simplicity, high optical throughput, and efficient data acquisition, which would pave a novel way for NIR spectral imaging in biomedical diagnostics and material characterization.