Computational intelligence for remote sensing /

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Bibliographic Details
Imprint:Berlin : Springer, ©2008.
Description:1 online resource (x, 391 pages) : illustrations.
Language:English
Series:Studies in computational intelligence ; v. 133
Studies in computational intelligence ; v. 133.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11070070
Hidden Bibliographic Details
Other authors / contributors:Graña, Manuel, 1958-
Duro, Richard J., 1965-
ISBN:9783540793533
3540793534
9783540793526
3540793526
Notes:Includes bibliographical references and index.
Print version record.
Summary: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.
Other form:Print version: Computational intelligence for remote sensing. Berlin : Springer, ©2008 9783540793526 3540793526

MARC

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490 1 |a Studies in computational intelligence ;  |v v. 133 
504 |a Includes bibliographical references and index. 
505 0 0 |t Optical configurations for imaging spectrometers /  |r X. Prieto-Blanco [and others] --  |t Remote sensing data compression /  |r Joan Serra-Sagristà, Francesc Aulí-Llinàs --  |t A multiobjective evolutionary algorithm for hyperspectral image watermarking /  |r D. Sal, M. Graña --  |t Architecture and services for computational intelligence in remote sensing /  |r Sergio D'Elia [and others] --  |t On content-based image retrieval systems for hyperspectral remote sensing images /  |r Miguel A. Veganzones, José Orlando Maldenado, Manuel Graña --  |t An analytical approach to the optimal deployment of wireless sensor networks /  |r J. Vales-Alonso [and others] --  |t Parallel spatial-spectral processing of hyperspectral images /  |r Antonio J. Plaza --  |t Parallel classification of hyperspectral images using neural networks /  |r Javier Plaza [and others] --  |t Positioning weather systems from remote sensing data using genetic algorithms /  |r Wong Ka Yan, Yip Chi Lap --  |t A computation reduced technique to primitive feature extraction for image information mining via the use of wavelets /  |r Vijay P. Shah [and others] --  |t Neural networks for land cover applications /  |r Fabio Pacifici [and others] --  |t Information extraction for forest fire management /  |r Andrea Pelizzari Ricardo Armas Goncalves, Mario Caetano --  |t Automatic preporocessing and classification system for high resolution ultra and hyperspectral images /  |r Abraham Prieto [and others] --  |t Using Gaussian synapse ANNs for hyperspectral image segmentation and endmember extraction /  |r R.J. Duro, F. Lopez-Pena, J.L. Crespo --  |t Unsupervised change detection from multichannel SAR data by Markov random fields /  |r Sebastiano B. Serpico, Gabriele Moser. 
588 0 |a Print version record. 
520 |a 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. 
650 0 |a Remote sensing  |x Mathematics.  |0 http://id.loc.gov/authorities/subjects/sh85112800 
650 0 |a Remote-sensing images.  |0 http://id.loc.gov/authorities/subjects/sh94003667 
650 0 |a Computational intelligence.  |0 http://id.loc.gov/authorities/subjects/sh94004659 
650 0 |a Genetic algorithms.  |0 http://id.loc.gov/authorities/subjects/sh92002377 
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650 0 7 |a Genetic algorithms.  |2 cct 
650 0 7 |a Remote sensing  |x Mathematics.  |2 cct 
650 0 7 |a Remote-sensing images.  |2 cct 
650 7 |a Ingénierie.  |2 eclas 
650 7 |a Computational intelligence.  |2 fast  |0 (OCoLC)fst00871995 
650 7 |a Genetic algorithms.  |2 fast  |0 (OCoLC)fst00939996 
650 7 |a Remote-sensing images.  |2 fast  |0 (OCoLC)fst01094509 
650 7 |a Remote sensing  |x Mathematics.  |2 fast  |0 (OCoLC)fst01094490 
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700 1 |a Duro, Richard J.,  |d 1965-  |0 http://id.loc.gov/authorities/names/n2002153851  |1 http://viaf.org/viaf/85225028 
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