Hierarchical segmentation of polarimetric SAR images using heterogeneous clutter models

  • Bombrun L
  • Vasile G
  • Gay M
 et al. 
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Abstract

In this paper, heterogeneous clutter models are used to describe polarimetric synthetic aperture radar (PolSAR) data. The KummerU distribution is introduced to model the PolSAR clutter. Then, a detailed analysis is carried out to evaluate the potential of this new multivariate distribution. It is implemented in a hierarchical maximum likelihood segmentation algorithm. The segmentation results are shown on both synthetic and high-resolution PolSAR data at the X- and L-bands. Finally, some methods are examined to determine automatically the “optimal” number of segments in the final partition.

Author-supplied keywords

  • Fisher probability density function (PDF)
  • KummerU PDF
  • polarimetric synthetic aperture radar (PolSAR) data
  • segmentation
  • spherically invariant random vectors (SIRV)

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Authors

  • Lionel Bombrun

  • Gabriel Vasile

  • Michel Gay

  • Felix Totir

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