Classification Methods for Remotely Sensed Data

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Classification Methods for Remotely...

Classification Methods for Remotely Sensed Data

Name: Classification Methods for Remotely Sensed Data
ISBN: 9781420090727

Paul Mather, Brandt Tso

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This comprehensive emphasizes new methods involved in the extraction of thematic information from remotely sensed images, including neural networks (especially artificial neural networks), fuzzy theory, texture and quantization, and the use of Markov random fields. It is concise and accessible and the authors conclude with coverage of the state-of-the-art topics of multisource data analysis, evidential reasoning and genetic algorithms. Including a full color section and basic remote sensing theory, Classification Methods for Remotely Sensed Data will prove invaluable for advanced undergraduate students and graduates/researchers in the field.

Categorías:

Engineering

Año:

2009

Edición:

Editorial:

CRC Press

Idioma:

english

Páginas:

376

ISBN 10: