Laser & Optoelectronics Progress, Volume. 57, Issue 1, 013003(2020)
Multispectral Dimension Reduction Algorithm Based on Partial Least Squares
Fig. 1. Chromaticity diagrams of 1600 Munsell color blocks obtained by CIE D65 and CIE 1931 standard observers. (a) L*-a* chromaticity diagram; (b) L*-b* chromaticity diagram; (c) a*-b* chromaticity diagram
Fig. 2. Spectral error distributions obtained by different dimension reduction methods. (a) Dimension reduction by LabPQR method; (b) dimension reduction by LabKMN method
Fig. 3. Spectral reconstruction RMSE curves obtained by different dimension reduction methods. (a) Dimension reduction by LabPQR method; (b) dimension reduction by LabKMN method
Fig. 4. Fitted curves of reconstructed spectra for different samples. (a) Sample with good fitted effect; (b) sample with general fitted effect; (c) sample with poor fitted effect
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Qiulan Yang, Xiaoxia Wan, Gensheng Xiao. Multispectral Dimension Reduction Algorithm Based on Partial Least Squares[J]. Laser & Optoelectronics Progress, 2020, 57(1): 013003
Category: Spectroscopy
Received: Jun. 4, 2019
Accepted: Jul. 22, 2019
Published Online: Jan. 3, 2020
The Author Email: Wan Xiaoxia (wan@whu.edu.com)