Fuzzy Cognitive Maps Applied to Synthetic Aperture Radar Image Classifications

  • Gonzalo Pajares
  • Javier Sánchez-Lladó
  • Carlos López-Martínez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6915)


This paper proposes a method based on Fuzzy Cognitive Maps (FCM) for improving the classification provided by the Wishart maximum-likelihood based approach in Synthetic Aperture Radar (SAR) images. FCM receives the classification results provided by the Wishart approach and creates a network of nodes associating a pixel to a node. The activation levels of these nodes define the degree of membeship of each pixel to each class. These activations levels are iteratively reinforced or punished based on the existing relations among each node and its neighbours and also taking into account the own node under consideration. Through a quality coefficient we measure the performance of the proposed approach with respect to the Wishart classifier.


Fuzzy Cognitive Maps Wishart classifier Synthetic Aperture Radar (SAR) Polarimetric SAR (POLSAR) classification 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Gonzalo Pajares
    • 1
  • Javier Sánchez-Lladó
    • 2
  • Carlos López-Martínez
    • 2
  1. 1.Dpto. Ingeniería del Software e Inteligencia Artificial, Facultad de InformáticaUniversity Complutense of MadridMadridSpain
  2. 2.Remote Sensing Laboratory (RSLab), Signal Theory and Communications DepartmentUniversitat Politècnica de Catalunya (UPC)BarcelonaSpain

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