• DocumentCode
    1549386
  • Title

    Filtering of multichannel SAR images

  • Author

    Quegan, Shaun ; Yu, Jiong Jiong

  • Author_Institution
    Centre for Earth Obs. Sci., Univ. of Sheffield, UK
  • Volume
    39
  • Issue
    11
  • fYear
    2001
  • fDate
    11/1/2001 12:00:00 AM
  • Firstpage
    2373
  • Lastpage
    2379
  • Abstract
    An explicit form of the linear multichannel synthetic aperture radar (SAR) intensity filter, which preserves radiometry while optimally reducing speckle is derived, together with a compact expression for the theoretical gain in equivalent numbers of looks (ENLs). The filter can be applied to mixed data types, which is demonstrated using a combination of ERS and JERS satellite data, and confirms the filter performance predicted by the theory. Tests indicate that a simplified form of the filter, which neglects correlation between images, gives an ENL only slightly less than optimal, while being much easier to implement. Exact analysis of the effect of estimating filter weights shows that the linear increase in ENL with the number of images predicted for the ideal filter does not occur. In practice, the ENL is affected by the window size used to estimate the weights and saturates as the number of images increases. An efficient recursive form of the filter is described, which is most naturally applied to multitemporal data for the practically important case where the current image is uncorrelated with previous images in a data sequence
  • Keywords
    agriculture; forestry; remote sensing by radar; synthetic aperture radar; vegetation mapping; ERS data; JERS data; SAR data; agriculture; equivalent number of looks; filter performance; forestry; linear multichannel synthetic aperture radar intensity filter; mixed data types; multichannel SAR images; multitemporal data; multitemporal filtering; optimally reducing speckle; radiometry; satellite data; speckle reduction; Data mining; Filtering theory; Forestry; Image analysis; Nonlinear filters; Radiometry; Satellite broadcasting; Speckle; Synthetic aperture radar; Testing;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.964973
  • Filename
    964973