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

Authors:
Fabio Pacifici;William J. Emery
Affiliations:
Department of Computer, Systems and Production Engineering, Tor Vergata University, Rome, Italy;Department of Aerospace Engineering Science, University of Colorado at Boulder, USA
Venue:
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Year:
2009

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Abstract

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.