Advertisement

Computational Intelligence for Remote Sensing

  • Editors
  • Manuel Graña
  • Richard J. Duro

Part of the Studies in Computational Intelligence book series (SCI, volume 133)

Table of contents

  1. Front Matter
  2. X. Prieto-Blanco, C. Montero-Orille, B. Couce, R. de la Fuente
    Pages 1-25
  3. Joan Serra-Sagristà, Francesc Aulí-Llinàs
    Pages 27-61
  4. Sergio D’Elia, Pier Giorgio Marchetti, Yves Coene, Steven Smolders, Andrea Colapicchioni, Claudio Rosati
    Pages 79-123
  5. Miguel A. Veganzones, José Orlando Maldonado, Manuel Graña
    Pages 125-144
  6. J. Vales-Alonso, S. Costas-Rodríguez, M. V. Bueno-Delgado, E. Egea-López, F. Gil-Castiñeira, P. S. Rodríguez-Hernández et al.
    Pages 145-161
  7. Javier Plaza, Antonio Plaza, Rosa Pérez, Pablo Martínez
    Pages 193-216
  8. Vijay P. Shah, Nicolas H. Younan, Surya H. Durbha, Roger L. King
    Pages 245-266
  9. Fabio Pacifici, Fabio Del Frate, Chiara Solimini, William J. Emery
    Pages 267-293
  10. Andrea Pelizzari, Ricardo Armas Goncalves, Mario Caetano
    Pages 295-312
  11. Abraham Prieto, Francisco Bellas, Fernando Lopez-Pena, Richard J. Duro
    Pages 313-340
  12. Sebastiano B. Serpico, Gabriele Moser
    Pages 363-388
  13. Back Matter

About this book

Introduction

This book is a composition of different points of view regarding the application of Computational Intelligence techniques and methods to Remote Sensing data and applications. It is the general consensus that classification, its related data processing, and global optimization methods are core topics of Computational Intelligence. Much of the content of the book is devoted to image segmentation and recognition, using diverse tools from different areas of the Computational Intelligence field, ranging from Artificial Neural Networks to Markov Random Field modeling. The book covers a broad range of topics, starting from the hardware design of hyperspectral sensors, and data handling problems, namely data compression and watermarking issues, as well as autonomous web services. The main contents of the book are devoted to image analysis and efficient (parallel) implementations of these analysis techniques. The classes of images dealt with throughout the book are mostly multispectral-hyperspectral images, though there are some instances of processing Synthetic Aperture Radar images.

Keywords

Markov Markov random field classification cognition computational intelligence evolutionary algorithm genetic algorithms image analysis image segmentation intelligence modeling neural networks optimization remote sensing sensing

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-79353-3
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-79352-6
  • Online ISBN 978-3-540-79353-3
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site