Fast hyperspectral imager driven by a low-cost and compact galvo-mirror

被引:9
|
作者
Liu, Xiaomei [1 ]
Jiang, Ziqi [1 ]
Wang, Tianci [1 ]
Cai, Fuhong [1 ,2 ]
Wang, Dan [3 ]
机构
[1] Hainan Univ, Mech & Elect Engn Coll, Haikou 570228, Hainan, Peoples R China
[2] Hainan Univ, Sch Biomed Engn, Haikou 570228, Hainan, Peoples R China
[3] Beijing Univ Chem Technol, State Key Lab Organ Inorgan Composites, Beijing 100029, Peoples R China
来源
OPTIK | 2020年 / 224卷
基金
海南省自然科学基金;
关键词
Galvo-mirror scanning; Imaging spectrometer; High speed; IDENTIFICATION; CLASSIFICATION;
D O I
10.1016/j.ijleo.2020.165716
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Imaging spectrometer is a critical device for remote sensing in visible and infrared band. Nowadays, it has become a powerful instrument to obtain three-dimensional hyperspectral cube (two-dimensional spatial information and one-dimensional spectral information) of targets for high precision object recognition. However, we often cannot meet the requirements of high spatial resolution and high spectral resolution at the same time. So there is still a trade-off between detection speed and data accuracy (including spatial and spectral resolution). In this paper, we developed a fast and high spectral resolution imaging spectrometer to obtain the spectral spatial information with the help of a low-cost and compact galvo-mirror. The spectrometer has a wavelength resolution of about 10 nm at visible-near infrared band (400 nm-800 nm), and it can measure two-dimensional spatial images of various biological samples (including corals, dragon fruits and human hands) at various wavelengths repeatedly. This spectrometer can facilitate collection of a large number of spectral image data during half cycle of galvo-mirror scanning. The theoretical acquisition speed of hyperspectral cube can reach more than 1 MHz. However, at this acquisition speed, the signal-to-noise ratio of the camera is poor, and it is unable to obtain high-quality signals. We believe that with the improvement of camera performance, our prototype can obtain hyperspectral data at a higher sampling speed.
引用
收藏
页数:7
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