Computational intelligence for remote sensing

✍ Scribed by X. Prieto-Blanco, C. Montero-Orille (auth.), Manuel Graña, Richard J. Duro (eds.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2008
• Tongue: English
• Leaves: 397
• Series: Studies in Computational Intelligence 133
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages -
Optical Configurations for Imaging Spectrometers....Pages 1-25
Remote Sensing Data Compression....Pages 27-61
A Multiobjective Evolutionary Algorithm for Hyperspectral Image Watermarking....Pages 63-78
Architecture and Services for Computational Intelligence in Remote Sensing....Pages 79-123
On Content-Based Image Retrieval Systems for Hyperspectral Remote Sensing Images....Pages 125-144
An Analytical Approach to the Optimal Deployment of Wireless Sensor Networks....Pages 145-161
Parallel Spatial-Spectral Processing of Hyperspectral Images....Pages 163-192
Parallel Classification of Hyperspectral Images Using Neural Networks....Pages 193-216
Positioning Weather Systems from Remote Sensing Data Using Genetic Algorithms....Pages 217-243
A Computation Reduced Technique to Primitive Feature Extraction for Image Information Mining Via the Use of Wavelets....Pages 245-266
Neural Networks for Land Cover Applications....Pages 267-293
Information Extraction for Forest Fires Management....Pages 295-312
Automatic Preprocessing and Classification System for High Resolution Ultra and Hyperspectral Images....Pages 313-340
Using Gaussian Synapse ANNs for Hyperspectral Image Segmentation and Endmember Extraction....Pages 341-362
Unsupervised Change Detection from Multichannel SAR Data by Markov Random Fields....Pages 363-388
Back Matter....Pages -

✦ Subjects

Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics)