Acta Optica Sinica, Volume. 41, Issue 6, 0610001(2021)

Hyperspectral Image Classification Based on Local Gaussian Mixture Feature Extraction

Dan Li1,2、*, Fanqiang Kong2, and Deyan Zhu1,2
Author Affiliations
  • 1Key Laboratory of Space Photoelectric Detection and Perception, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016, China
  • 2College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016, China
  • show less
    References(26)

    [3] Li J. Bioucas-Dias J M, Plaza A. Semisupervised hyperspectral image segmentation using multinomial logistic regression with active learning[J]. IEEE Transactions on Geoscience and Remote Sensing, 48, 4085-4098(2010).

    [6] Chen Y, Nasrabadi N M, Tran T D. Hyperspectral image classification using dictionary-based sparse representation[J]. IEEE Transactions on Geoscience and Remote Sensing, 49, 3973-3985(2011).

    [7] Chen Y S, Jiang H L, Li C Y et al. Deep feature extraction and classification of hyperspectral images based on convolutional neural networks[J]. IEEE Transactions on Geoscience and Remote Sensing, 54, 6232-6251(2016).

    [19] Lee H, Kwon H. Going deeper with contextual CNN for hyperspectral image classification[J]. IEEE Transactions on Image Processing, 26, 4843-4855(2017).

    Tools

    Get Citation

    Copy Citation Text

    Dan Li, Fanqiang Kong, Deyan Zhu. Hyperspectral Image Classification Based on Local Gaussian Mixture Feature Extraction[J]. Acta Optica Sinica, 2021, 41(6): 0610001

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Image Processing

    Received: Sep. 29, 2020

    Accepted: Nov. 5, 2020

    Published Online: Apr. 7, 2021

    The Author Email: Li Dan (danli@nuaa.edu.cn)

    DOI:10.3788/AOS202141.0610001

    Topics