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SpectraTrack:百万像素、百帧每秒和千通道高光谱成像。

SpectraTrack: megapixel, hundred-fps, and thousand-channel hyperspectral imaging.

作者信息

Li Daoyu, Wu Jinxuan, Zhao Jiajun, Xu Hanwen, Bian Liheng

机构信息

State Key Laboratory of CNS/ATM & MIIT Key Laboratory of Complex-field Intelligent Sensing, Beijing Institute of Technology, 100081, Beijing, China.

出版信息

Nat Commun. 2024 Nov 1;15(1):9459. doi: 10.1038/s41467-024-53747-8.

Abstract

Hyperspectral imaging (HSI) finds broad applications in various fields due to its substantial optical signatures for the intrinsic identification of physical and chemical characteristics. However, it faces the inherent challenge of balancing spatial, temporal, and spectral resolution due to limited bandwidth. Here we present SpectraTrack, a computational HSI scheme that simultaneously achieves high spatial, temporal, and spectral resolution in the visible-to-near-infrared (VIS-NIR) spectral range. We deeply investigated the spatio-temporal-spectral multiplexing principle inherent in HSI videos. Based on this theoretical foundation, the SpectraTrack system uses two cameras including a line-scan imaging spectrometer for temporal-multiplexed hyperspectral data and an auxiliary RGB camera to capture motion flow. The motion flow guides hyperspectral reconstruction by reintegrating the scanned spectra into a 4D video. The SpectraTrack system can achieve around megapixel HSI at 100 fps with 1200 spectral channels, demonstrating its great application potential from drone-based anti-vibration video-rate HSI to high-throughput non-cooperative anti-spoofing.

摘要

高光谱成像(HSI)因其对物理和化学特征的内在识别具有大量光学特征而在各个领域有着广泛应用。然而,由于带宽有限,它面临着平衡空间、时间和光谱分辨率这一固有挑战。在此,我们提出了SpectraTrack,一种计算高光谱成像方案,它能在可见光到近红外(VIS-NIR)光谱范围内同时实现高空间、时间和光谱分辨率。我们深入研究了高光谱成像视频中固有的时空光谱复用原理。基于这一理论基础,SpectraTrack系统使用两台相机,其中一台线扫描成像光谱仪用于时间复用的高光谱数据采集,另一台辅助RGB相机用于捕捉运动流。运动流通过将扫描光谱重新整合到一个4D视频中来引导高光谱重建。SpectraTrack系统能够以100帧/秒的速度实现约百万像素的高光谱成像,具备1200个光谱通道,这表明其在基于无人机的抗振动视频速率高光谱成像到高通量非合作反欺骗等方面具有巨大的应用潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6c0/11530457/2cbe11ee5722/41467_2024_53747_Fig1_HTML.jpg

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