基于时空复用的红外单像素高光谱成像
Infrared Single-Pixel Hyperspectral Imaging via Spatial-Temporal Multiplexing
AI总结：
提出一种基于频谱-时间映射和空间编码压缩测量的单像素近红外高光谱成像系统，实现50个光谱波段的高光谱数据立方体重建和动态过程实时监测。
摘要：
近红外高光谱成像被广泛用于揭示形态和化学信息。然而，传统光谱成像仪通常依赖昂贵的焦平面阵列，并存在空间-光谱数据采集的数据冗余和低效问题。本文设计并实现了一种基于高保真频谱-时间映射和高精度空间编码压缩测量的单像素近红外高光谱成像系统。该系统采用单模通信光纤进行时间色散，并使用可编程空间光调制器施加结构化空间图案，所有信号由单个InGaAs光电探测器检测。通过将时间拉伸波形与空间编码相关联，我们重建了64×64空间分辨的高光谱数据立方体，覆盖1550-1600 nm范围内的50个光谱波段。此外，在亚奈奎斯特采样下，以12 Hz的数据立方体刷新率演示了动态液体注入的实时监测。所提出的架构具有单像素简单性、高光通量和高效数据采集的特点，将为生物医学诊断和材料表征中的近红外光谱成像开辟新途径。
英文摘要：
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.
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