高光谱成像
计算机科学
人工智能
成像光谱仪
快照(计算机存储)
计算机视觉
全光谱成像
软件可移植性
光谱成像
化学成像
图像分辨率
影像学
遥感
光学
分光计
物理
操作系统
地质学
程序设计语言
作者
Haiquan Hu,Hao Zhou,Zhihai Xu,Qi Li,Huajun Feng,Yueting Chen,Tingting Jiang,Wenbin Xu
标识
DOI:10.1016/j.optlaseng.2022.107098
摘要
As the pursuit of snapshot spectral imaging continued to grow, traditional hyperspectral imaging systems have been too enormous and too slow to implement in real scenarios. Considering the portability and the demand for snapshots, in this study, we proposed a practical hyperspectral camera with a designed diffractive optical element (DOE). The designed DOE distinguished the incident spectrums and converged them into different point spread functions (PSFs) on the imaging plane. Utilizing the spectrally-varying PSF information, we engaged the iterative algorithm with the deep-learning model to reconstruct hyperspectral data. Experimental results demonstrated that the proposed system performed at least as well as the current methods and could achieve great spatial resolution and spectral accuracy in spectral imaging. This proposed system had good potential in portable hyperspectral imaging system.
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