• Opto-Electronic Engineering
  • Vol. 39, Issue 2, 63 (2012)
PENG Yan-bin1、* and AI Jie-qing2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3969/j.issn.1003-501x.2012.02.013 Cite this Article
    PENG Yan-bin, AI Jie-qing. Hyperspectral Imagery Classification Based on Spectral Clustering Band Selection[J]. Opto-Electronic Engineering, 2012, 39(2): 63 Copy Citation Text show less
    References

    [2] MELGANI F,BRUZZONE L. Classification of hyperspectral remote sensing images with support vector machines [J]. IEEE Transactions on Geoscience and Remote Sensing(S0196-2892),2004,42(8):1778-1790.

    [4] MARTíNEZ-USó A,PLA F,SOTOCA J M,et al. Clustering-based hyperspectral band selection using information measures [J]. IEEE Transactions on Geoscience and Remote Sensing(S0196-2892),2007,45(12):4158-4171.

    [5] CHEIN-I CHANG,QIAN DU,TZU-LUNG SUN,et al. A joint band prioritization and band-decorrelation approach to band selection for hyperspectral image classification [J]. IEEE Transactions on Geoscience and Remote Sensing(S0196-2892), 1999,37(6):2631-2641.

    [6] QIAN Y,YAO F,JIA S. Band selection for hyperspectral imagery using affinity propagation [J]. IET Computer Vision(S1751-9632),2009,3(4):213-222.

    [7] CHENG Q,VARSHNEY P K,ARORA M K. Logistic regression for feature selection and soft classification of remote sensing data [J]. IEEE Geoscience and Remote Sensing Letters(S1545-598X),2006,3(4):491-494.

    [8] LI Ji-ming,QIAN Yun-tao. Clustering-based hyperspectral band selection using sparse nonnegative matrix factorization [J]. Journal of Zhejiang University-Science C(S1869-196X ),2011,12(7):542-549.

    [10] VON LUXBURG U. A tutorial on spectral clustering [J]. Statistics and Computing(S0960-3174 ),2007,17(4):395-416.

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    PENG Yan-bin, AI Jie-qing. Hyperspectral Imagery Classification Based on Spectral Clustering Band Selection[J]. Opto-Electronic Engineering, 2012, 39(2): 63
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