Pulse Coupled Neural Networks for Automatic Urban Change Detection at Very High Spatial Resolution

  • Fabio Pacifici
  • William J. Emery
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)


In this paper, a novel unsupervised approach based on Pulse-Coupled Neural Networks (PCNNs) for image change detection is discussed. PCNNs are based on the implementation of the mechanisms underlying the visual cortex of small mammals and with respect to more traditional neural networks architectures own interesting advantages. In particular, they are unsupervised and context sensitive. The performance of the algorithm has been evaluated on very high spatial resolution QuickBird and WorldView-1 images. Qualitative and more quantitative results are discussed.


Change detection Pulse Coupled Neural Networks Urban Environment 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Fabio Pacifici
    • 1
  • William J. Emery
    • 2
  1. 1.Department of Computer, Systems and Production EngineeringTor Vergata UniversityRomeItaly
  2. 2.Department of Aerospace Engineering ScienceUniversity of Colorado at BoulderUSA

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