Classification Methods for Remotely Sensed Data

ISBN-13: 9781420090727 / Angielski / Twarda / 2009 / 376 str.

Brandt Tso; Paul Mather

Opis

The field of pattern recognition is expanding in new directions, for example, in data mining and Earth observation data processing. This book covers the entire field of classification methods applied to remotely sensed data. After an introduction to the basics of remote sensing, the text provides a detailed discussion of different approaches to image classification, including maximum likelihood, fuzzy sets, and artificial neural networks. The second edition features three new chapters that cover recent developments in support vector machines, decision trees, as well as change detection and mixed pixel classification. It also updates references and discussions of Earth observation missions.

Recenzje

… a very useful addition to the shelf of anyone engaged in remote sensing image analysis. It is suitable for both students and practitioners.
—Michael Collins,  in GEOMATICA, Vol. 63, No. 4

Spis treści

Remote Sensing in the Optical and Microwave Regions. Pattern Recognition Principles. Artificial Neural Networks. Support Vector Machines. Methods Based on Fuzzy Set Theory. Decision Trees. Texture Quantization. Modeling Context Using Markov Random Fields. Multisource Classification. Bibliography. Index.

O autorze

Paul Mather, Brandt Tso