SAR Image Segmentation Using Level Sets and Region Competition under the \(\mathcal{G}^H\) Model

  • Maria Elena Buemi
  • Norberto Goussies
  • Julio Jacobo
  • Marta Mejail
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)

Abstract

Synthetic Aperture Radar (SAR) images are dificult to segment due to their characteristic noise, called speckle, which is multiplicative, non-gaussian and has a low signal to noise ratio. In this work we use the \(\mathcal{G}^{H}\) distribution to model the SAR data from the different regions of the image. We estimate their statistical parameters and use them in a segmentation algorithm based on multiregion competition. We then apply this algorithm to segment simulated as well as real SAR images and evaluate the accuracy of the segmentation results obtained.

Keywords

SAR images \(\mathcal{G}^{H}\)distribution multiregion competition level set segmentation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Maria Elena Buemi
    • 1
  • Norberto Goussies
    • 1
  • Julio Jacobo
    • 1
  • Marta Mejail
    • 1
  1. 1.Departamento de Computación, Facultad de Ciencias Exactas y NaturalesUniversidad de Buenos AiresCiudad de Buenos AiresRepública Argentina

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