ACA Multiagent System for Satellite Image Classification

  • Moisés Espínola
  • José A. Piedra
  • Rosa Ayala
  • Luís Iribarne
  • Saturnino Leguizamón
  • Massimo Menenti
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 157)


In this paper, we present a multiagent system for satellite image classification. With this aim we will describe a new classification algorithm based on cellular automata called ACA (Algorithm based on Cellular Automata). This algorithm can be modeled by agents. Actually, there are different classification algorithms, such as minimum distance and parallelepiped classifiers, but none is fullreliable in terms of quality. One of the main advantages of ACA is to provide a mechanism which offers a hierarchical classification divided into levels of reliability with a final quality optimized through contextual techniques. Finally, we have developed a multiagent system which allows to classify satellite images in the SOLERES framework.


Satellite Image Contextual Information Cellular Automaton Multiagent System Noisy Pixel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Moisés Espínola
    • 1
  • José A. Piedra
    • 1
  • Rosa Ayala
    • 1
  • Luís Iribarne
    • 1
  • Saturnino Leguizamón
    • 2
  • Massimo Menenti
    • 3
  1. 1.Applied Computing GroupUniversity of AlmeríaAlmeriaSpain
  2. 2.Regional Faculty of MendozaNational Technnological UniversityVariousArgentina
  3. 3.Aerospace Engineering Optical and Laser Remote SensingTUDelftDelftThe Netherlands

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