Multidimensional Systems and Signal Processing

, Volume 21, Issue 4, pp 319–342 | Cite as

Polarimetric SAR image segmentation with B-splines and a new statistical model

  • Alejandro C. Frery
  • Julio Jacobo-Berlles
  • Juliana Gambini
  • Marta E. Mejail


We present an approach for polarimetric Synthetic Aperture Radar (SAR) image region boundary detection based on the use of B-Spline active contours and a new model for polarimetric SAR data: the \({\mathcal{G}_P^H}\) distribution. In order to detect the boundary of a region, initial B-Spline curves are specified, either automatically or manually, and the proposed algorithm uses a deformable contours technique to find the boundary. In doing this, the parameters of the polarimetric \({\mathcal{G}_P^H}\) model for the data are estimated, in order to find the transition points between the region being segmented and the surrounding area. This is a local algorithm since it works only on the region to be segmented. Results of its performance are presented.


Polarimetric signal analysis Synthetic aperture radar Complex-valued sensing Edge detection Statistical model Specklenoise Estimation B-spline curves 


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Alejandro C. Frery
    • 1
  • Julio Jacobo-Berlles
    • 2
  • Juliana Gambini
    • 2
  • Marta E. Mejail
    • 2
  1. 1.Instituto de ComputaçãoUniversidade Federal de AlagoasMaceióBrazil
  2. 2.Departamento de ComputaciónUniversidad de Buenos AiresBuenos AiresArgentina

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