Fuzzy cognitive maps applied to synthetic aperture radar image classifications

  • Authors:

  • Gonzalo Pajares;Javier Sánchez-Lladó;Carlos López-Martínez

  • Affiliations:

  • Dpto. Ingeniería del Software e Inteligencia Artificial, Facultad de Informática, University Complutense of Madrid, Madrid, Spain;Remote Sensing Laboratory, Signal Theory and Communications Department, Universitat Politècnica de Catalunya, Barcelona, Spain;Remote Sensing Laboratory, Signal Theory and Communications Department, Universitat Politècnica de Catalunya, Barcelona, Spain

  • Venue:
  • ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
  • Year:
  • 2011

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Abstract

This paper proposes a method based on Fuzzy Cognitive Maps (FCM) for improving the classification provided by the Wishart maximumlikelihood 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.