Citation: LI Xue-Ying,  REN Guo-Xing,  LYU Mei-Rong,  LIU Yan,  SUN Zhong-Liang,  HOU Guang-Li,  FAN Ping-Ping. Study on Calibration Transfer between Laboratory Spectrometer and Hyperspectral Camera[J]. Chinese Journal of Analytical Chemistry, ;2021, 49(9): 1580-1586. doi: 10.19756/j.issn.0253-3820.191165 shu

Study on Calibration Transfer between Laboratory Spectrometer and Hyperspectral Camera

  • Corresponding author: FAN Ping-Ping, fanpp_sdioi@126.com
  • Received Date: 29 March 2019
    Revised Date: 19 April 2021

    Fund Project: Supported by the National Natural Science Foundation of China (Nos.U2006209, 3130041) and the Shandong Provincial Natural Science Foundation, China (Nos.ZR2018LD007, ZR2017BB037).

  • Laboratory spectrometer is a spectrometer that can only obtain spectral signals by spectrometer, and hyperspectral camera acquires image and spectral information by image. Under the condition of using laboratory spectrometer, the calibration transfer of different temperatures, different ordinary spectrometers, different measuring conditions and samples from different regions has been studied. But there are few studies on the calibration transfer between laboratory spectrometer and hyperspectral camera. Taking 164 soil samples from Qingdao as an example, the spectral data of laboratory spectrometer and hyperspectral camera data were obtained in this work. The content models of total nitrogen (TN) and total phosphorus (TP) were established based on the spectral data of laboratory spectrometer. Three methods, namely piecewise direct correction algorithm, model updating and slope/bias correction (PDS-MP-S/B), were used to transfer the hyperspectral data. The transferred hyperspectral data were substituted into the content models of TN and TP to predict their content values and evaluate the prediction effect. Meanwhile, the influence of the number of PDS window and the number of standard set on the prediction results was analyzed. When the number of PDS window was 19 and the number of standard set was 120, the prediction effect after calibration transfer was the best, absolute coefficient of test set (Rt2) was 0.736 and root mean square error of prediction (RMSEP) was 0.274. In the content prediction of TP, when the number of PDS window was 23 and the number of standard set was 80, the prediction effect after calibration transfer was the best, Rt2 was 0.647 and RMSEP was 0.231. The solution of model transfer between laboratory spectrometers and hyperspectral cameras provided a powerful basis for rapid prediction of a large number of image information data collected by hyperspectral cameras, which greatly reduced the workload, and the wide application of hyperspectral cameras in quantitative analysis and rapid measurement technology.
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