Spectroscopy and Spectral Analysis, Volume. 44, Issue 1, 29(2024)
Training Sample Selection for Spectral Reconstruction Based on Improved K-Means Clustering
[1] [1] Day E A, Berns R S, Taplin L A, et al. Journal of Imaging Science and Technology, 2004, 48(2): 93.
[2] [2] Baribeau R. 1st Int Symposium on 3D Data Processing Vision, Graphics and Image Processing, 2003: 115.
[3] [3] Herzog P G, Knipp D, Stiebig H, et al. Journal of Electronic Imaging, 1999, 8(4): 342.
[4] [4] Dicarlo J M, Wandell B A. J. Opt. Soc. Am. A, 2003, 20(7): 1261.
[6] [6] Hardeberg J Y. Journal of Imaging Science and Technology, 2004, 48(2): 105.
[7] [7] Cheung V, Westland S. Journal of Imaging Science and Technology, 2006, 50(5): 481.
[8] [8] Mohammadi M,Nezamabadi M,Berns R S,et al. 12th Color Imaging Conference, 2004: 59.
[9] [9] Shen Huiliang, Han Tianqi, Li Chunguang. IEEE Transactions on Image Processing, 2017, 26(1): 439.
[10] [10] Liu Zhen, Liu Qiang, Gao Guiai, et al. Optics Express, 2017, 25(11): 12435.
[11] [11] Liu Zhen, Xiao Kaida, Pointer Michael R, et al. Sensors, 2021, 21(23): 7911.
[12] [12] Liang Jinxing, Xiao Kaida, Hu Xinrong. Optics Express, 2021, 29(26): 43899.
Get Citation
Copy Citation Text
LIU Zhen, LIU Li, FAN Shuo, ZHAO An-ran, LIU Si-lu. Training Sample Selection for Spectral Reconstruction Based on Improved K-Means Clustering[J]. Spectroscopy and Spectral Analysis, 2024, 44(1): 29
Received: Jun. 26, 2022
Accepted: --
Published Online: Jul. 31, 2024
The Author Email: Zhen LIU (zhen@whu.edu.cn)