Abstract Traditional fiber-optic spectrometers, while featuring compact designs and high sensitivity, are constrained to single-point spectral acquisition with limited spatial resolution, thereby restricting their broder applications. Although existing commercial spectral imaging systems can provide three-dimensional spectral cubes, they often require complex optical configurations, resulting in high costs and operational complexity. To overcome these limitations, this paper proposes a fiber-optic hyperspectral single-pixel imager (FHSPI) based on single-pixel computational imaging technology. In addition, by integrating a fiber-optic probe inspired by the compound eyes of insects, the FHSPI significantly expands the imaging field of view (FOV) to 130 degrees, representing a substantial increase from the 10-degree FOV of a single fiber. The FHSPI we proposed can achieve spectral image data cubes with a resolution of 1 nm, and by developing a spectral flux integration method, it enables high-quality spectral imaging under low-light conditions. Operating at a sub-0.1% sampling rate (0.09%), the FHSPI enables rapid distinguishing between authentic from artificial green leaves with a theoretical spectral identification speed of up to 1250 spectra per second (sp/s). We present a novel approach for developing cost-effective, high-performance fiber-optic spectral imaging technology that harnesses the potential advantages of FHSPI in addressing the data redundancy issues faced by conventional hyperspectral imagers. This advancement holds significant potential for fostering innovations in various applications, including precision agriculture, environmental monitoring, and biomedical diagnostics.
Chen et al. (Tue,) studied this question.