Overview
- Presents recent results in computational intelligence applications in remote sensing
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 133)
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Table of contents (15 chapters)
Keywords
About this book
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.
Bibliographic Information
Book Title: Computational Intelligence for Remote Sensing
Editors: Manuel Graña, Richard J. Duro
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-79353-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
Hardcover ISBN: 978-3-540-79352-6Published: 05 June 2008
Softcover ISBN: 978-3-642-09823-9Published: 19 November 2010
eBook ISBN: 978-3-540-79353-3Published: 08 September 2008
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: X, 393
Topics: Mathematical and Computational Engineering, Artificial Intelligence