Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data /
The main objective of this book is to apprise the reader of the use of a number of tools and techniques for a variety of image processing tasks, namely Independent Component Analysis (ICA), Mutual Information (MI), Markov Random Field (MRF) Models and Support Vector Machines (SVM). Typical applicati...
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| Format: | eBook |
| Language: | English |
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Berlin, Heidelberg :
Springer Berlin Heidelberg,
2004.
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| Online Access: | Connect to the full text of this electronic book |
| Summary: | The main objective of this book is to apprise the reader of the use of a number of tools and techniques for a variety of image processing tasks, namely Independent Component Analysis (ICA), Mutual Information (MI), Markov Random Field (MRF) Models and Support Vector Machines (SVM). Typical applications considered are feature extraction, image classification, image fusion and change detection. The book also treats a number of experimental examples based on a variety of remote sensors. The utility of the book will be highly appreciated by academicians and R & D professionals, who are involved in current research in the area of hyperspectral imaging, as well as by professional remote-sensing data users such as geologists, hydrologists, environmental scientists, civil engineers and computer scientists. |
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| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource (xv, 323 pages) |
| ISBN: | 9783662056059 (electronic bk.) 3662056054 (electronic bk.) |