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

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Abstract

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.

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Authors and Affiliations

  1. Instituto de Computação, Universidade Federal de Alagoas, Maceió, Brazil

    Alejandro C. Frery

  2. Departamento de Computación, Universidad de Buenos Aires, Buenos Aires, Argentina

    Julio Jacobo-Berlles, Juliana Gambini & Marta E. Mejail

Authors
  1. Alejandro C. Frery
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  2. Julio Jacobo-Berlles
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  3. Juliana Gambini
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  4. Marta E. Mejail
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Correspondence to Alejandro C. Frery.

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Frery, A.C., Jacobo-Berlles, J., Gambini, J. et al. Polarimetric SAR image segmentation with B-splines and a new statistical model. Multidim Syst Sign Process 21, 319–342 (2010). https://doi.org/10.1007/s11045-010-0113-4

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  • DOI: https://doi.org/10.1007/s11045-010-0113-4

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