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Chinese Optics Letters, Volume. 6, Issue 8, 558(2008)

Shrinkage-divergence-proximity locally linear embedding algorithm for dimensionality reduction of hyperspectral image

Qin Luo1, Zheng Tian1,2, and Zhixiang Zhao1
Author Affiliations
  • 1Department of Applied Mathematics, Northwestern Polytechnical University, Xi’an 710072
  • 2State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101
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    CLP Journals

    [1] Zhang Miao, Shen Yi, Wang Qiang. Nonlinear Correlation Coefficient Based Kernel Method for Hyperspectral Data Classification[J]. Acta Optica Sinica, 2009, 29(9): 2607

    Cited By

    [1] Jinhuan Wen, Zheng Tian, Hongwei She, Weidong Yan. Feature extraction of hyperspectral images based on preserving neighborhood discriminant embedding. 2010 International Conference on Image Analysis and Signal Processing, 257(2010).

    [2] Jinhuan Wen, Weidong Yan, Wei Lin. Supervised linear manifold learning feature extraction for hyperspectral image classification. 2014 IEEE Geoscience and Remote Sensing Symposium, 3710(2014).

    [3] Xiaojuan Xu, Jin Zhu, Zhihan Lv. Artistic Color Virtual Reality Implementation Based on Similarity Image Restoration. Complexity, 2021, 1(2021).

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    Qin Luo, Zheng Tian, Zhixiang Zhao. Shrinkage-divergence-proximity locally linear embedding algorithm for dimensionality reduction of hyperspectral image[J]. Chinese Optics Letters, 2008, 6(8): 558

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    Paper Information

    Received: Sep. 29, 2007

    Accepted: --

    Published Online: Sep. 2, 2008

    The Author Email:

    DOI:10.3788/COL20080608.0558

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology