• DocumentCode
    1607234
  • Title

    Application of AdaBoost in polarimetric SAR image classification

  • Author

    Min, Rui ; Yang, Xiaobo ; Zhao, Zhiqin

  • Author_Institution
    Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu
  • fYear
    2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, a method of polarimetric SAR image classification based on polarimetric decomposition and AdaBoost algorithm is proposed. The proposed method improves classification accuracy and speed. AdaBoost algorithm, as a robust learner with high accuracy, can fully utilize the polarimetric features to achieve image classification. In simulated tests, the proposed method is observed to produce improved classification accuracy and speed, compared with H /alphamacr classification algorithm.
  • Keywords
    feature extraction; image classification; learning (artificial intelligence); radar imaging; radar polarimetry; synthetic aperture radar; AdaBoost algorithm; polarimetric SAR image classification; robust learner; synthetic aperture radar; Boosting; Classification algorithms; Eigenvalues and eigenfunctions; Image classification; Matrix decomposition; Polarization; Robustness; Scattering; Synthetic aperture radar; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radar Conference, 2009 IEEE
  • Conference_Location
    Pasadena, CA
  • ISSN
    1097-5659
  • Print_ISBN
    978-1-4244-2870-0
  • Electronic_ISBN
    1097-5659
  • Type

    conf

  • DOI
    10.1109/RADAR.2009.4976988
  • Filename
    4976988