• DocumentCode
    41336
  • Title

    SAR Image Filtering Based on the Cauchy–Rayleigh Mixture Model

  • Author

    Qiangqiang Peng ; Long Zhao

  • Author_Institution
    Sci. & Technol. on Aircraft Control Lab., Beihang Univ., Beijing, China
  • Volume
    11
  • Issue
    5
  • fYear
    2014
  • fDate
    May-14
  • Firstpage
    960
  • Lastpage
    964
  • Abstract
    In this letter, a novel maximum a posteriori (MAP) filter for synthetic aperture radar (SAR) images is developed. We characterize the return signal of SAR using the Cauchy-Rayleigh mixture model, which is an approximation to the heavy-tailed Rayleigh distribution. The parameters of the Cauchy-Rayleigh mixture model are estimated from the noisy observation by using the expectation-maximization algorithm. Finally, we compare the proposed filter with several classical spatial filtering techniques by applying them on simulated data and various real SAR images. Experimental results show that the Cauchy-Rayleigh-mixture-based MAP filter performs better for speckle removal than the other methods, including Lee, Kuan, and Γ-MAP.
  • Keywords
    expectation-maximisation algorithm; radar imaging; synthetic aperture radar; Cauchy-Rayleigh mixture based MAP filter; Cauchy-Rayleigh mixture model; Rayleigh distribution; SAR image filtering; expectation-maximization algorithm; maximum a posteriori filter; real SAR images; simulated data; spatial filtering; speckle removal; synthetic aperture radar; Backscatter; Bayes methods; Filtering; Noise; Remote sensing; Speckle; Synthetic aperture radar; Mixture model; spatial filtering; speckle; synthetic aperture radar (SAR) image;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2013.2283258
  • Filename
    6623101