A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 9 Issue 6
Jun.  2022

IEEE/CAA Journal of Automatica Sinica

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Article Contents
H. C. Ji and Z. Y. Zuo, “Multiview locally linear embedding for spectral-spatial dimensionality reduction of hyperspectral imagery,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 6, pp. 1091–1094, Jun. 2022. doi: 10.1109/JAS.2022.105638
Citation: H. C. Ji and Z. Y. Zuo, “Multiview locally linear embedding for spectral-spatial dimensionality reduction of hyperspectral imagery,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 6, pp. 1091–1094, Jun. 2022. doi: 10.1109/JAS.2022.105638

Multiview Locally Linear Embedding for Spectral-Spatial Dimensionality Reduction of Hyperspectral Imagery

doi: 10.1109/JAS.2022.105638
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  • [1]
    R. Dian, S. Li, and X. Kang, “Regularizing hyperspectral and multispectral image fusion by CNN denoiser,” IEEE Trans. Neural Networks and Learning Systems, vol. 32, no. 3, pp. 1124–1135, 2021. doi: 10.1109/TNNLS.2020.2980398
    [2]
    L. Zhang, L. Zhang, D. Tao, and X. Huang, “On combining multiple features for hyperspectral remote sensing image classification,” IEEE Trans. Geoscience and Remote Sensing, vol. 50, no. 3, pp. 879–893, 2012. doi: 10.1109/TGRS.2011.2162339
    [3]
    Z. Cai and W. Zhu, “Feature selection for multi-label classification using neighborhood preservation,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 320–330, 2018. doi: 10.1109/JAS.2017.7510781
    [4]
    H. Abdi and L. J. Williams, “Principal component analysis,” Wiley Interdisciplinary Reviews: Computational Statistics, vol. 2, no. 4, pp. 433–459, 2010. doi: 10.1002/wics.101
    [5]
    Y. Wang, Z. Zhang, and Y. Lin, “Multi-cluster feature selection based on isometric mapping,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 570–572, 2022. doi: 10.1109/JAS.2021.1004398
    [6]
    S. T. Roweis and L. K. Saul, “Nonlinear dimensionality reduction by locally linear embedding,” Science, vol. 290, no. 5500, pp. 2323–2326, 2000. doi: 10.1126/science.290.5500.2323
    [7]
    M. Belkin and P. Niyogi, “Laplacian eigenmaps and spectral techniques for embedding and clustering,” Advances in Neural Information Processing Systems, vol. 14, pp. 585–591, 2001.
    [8]
    D. Hong, N. Yokoya, and X. X. Zhu, “Learning a robust local manifold representation for hyperspectral dimensionality reduction,” IEEE J. Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 6, pp. 2960–2975, 2017. doi: 10.1109/JSTARS.2017.2682189
    [9]
    G. Shi, H. Huang, and L. Wang, “Unsupervised dimensionality reduction for hyperspectral imagery via local geometric structure feature learning,” IEEE Geoscience and Remote Sensing Letters, vol. 17, no. 8, pp. 1425–1429, 2020. doi: 10.1109/LGRS.2019.2944970
    [10]
    X. Jiang, L. Xiong, Q. Yan, Y. Zhang, X. Liu, and Z. Cai, “Unsupervised dimensionality reduction for hyperspectral imagery via laplacian regularized collaborative representation projection,” IEEE Geoscience and Remote Sensing Letters, p. 6007805, 2022.
    [11]
    J. Wen, J. E. Fowler, M. He, Y.-Q. Zhao, C. Deng, and V. Menon, “Orthogonal nonnegative matrix factorization combining multiple features for spectral-spatial dimensionality reduction of hyperspectral imagery,” IEEE Trans. Geoscience and Remote Sensing, vol. 54, no. 7, pp. 4272–4286, 2016. doi: 10.1109/TGRS.2016.2539154
    [12]
    J. Jiang, J. Ma, C. Chen, Z. Wang, Z. Cai, and L. Wang, “SuperPCA: A superpixelwise PCA approach for unsupervised feature extraction of hyperspectral imagery,” IEEE Trans. Geoscience and Remote Sensing, vol. 56, no. 8, pp. 4581–4593, 2018. doi: 10.1109/TGRS.2018.2828029
    [13]
    T. Xia, D. C. Tao, T. Mei, and Y. D. Zhang, “Multiview spectral embedding,” IEEE Trans. Systems,Man,and Cybernetics,Part B (Cybernetics), vol. 40, no. 6, pp. 1438–1446, 2010. doi: 10.1109/TSMCB.2009.2039566
    [14]
    L. Zhang, L. P. Zhang, D. C. Tao, and X. Huang, “A modified stochastic neighbor embedding for multi-feature dimension reduction of remote sensing images,” ISPRS J. Photogrammetry and Remote Sensing, vol. 83, pp. 30–39, 2013.
    [15]
    R. Bhatia, Matrix Analysis. Berlin, Germany: Springer Science & Business Media, 2013, vol. 169, pp. 1–347.
    [16]
    M. Haghighat, S. Zonouz, and M. Abdel-Mottaleb, “CloudID: Trustworthy cloud-based and cross-enterprise biometric identification,” Expert Systems With Applications, vol. 42, no. 21, pp. 7905–7916, 2015. doi: 10.1016/j.eswa.2015.06.025

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