Signal Theory Methods in Multispectral Remote Sensing
Résumé
An outgrowth of the author's extensive experience teaching senior and graduate level students, this is both a thorough introduction and a solid professional reference.
- Material covered has been developed based on a 35-year research program associated with such systems as the Landsat satellite program and later satellite and aircraft programs.
- Covers existing aircraft and satellite programs and several future programs.
Contents
PART I: INTRODUCTION
- Introduction and Background
PART II: THE BASICS FOR CONVENTIONAL MULTISPECTRAL DATA
- Radiation and Sensor Systems in Remote Sensing
- Pattern Recognition in Remote Sensing
PART III: ADDITIONAL DETAILS
- Training a Classifier
- Hyperspectral Data Characteristics
- Feature Definition
- A Data Analysis Paradigm and Examples
- Use of Spatial Variations
- Noise in Remote Sensing Systems
- Multispectral Image Data Preprocessing
Appendix. An Outline of Probability Theory
L'auteur - David A. Landgrebe
DAVID A. LANDGREBE, PhD, is Professor Emeritus of
Electrical Computer Engineering in the School of Electrical
and Computer Engineering at Purdue University. Dr.
Landgrebe is a former president of the IEEE Geoscience and
Remote Sensing Society and recipient of the Society's
Distinguished Achievement Award. He is the coauthor of
Remote Sensing: The Quantitative Approach and a contributor
to numerous other publications.
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Wiley |
| Auteur(s) | David A. Landgrebe |
| Parution | 21/02/2003 |
| Nb. de pages | 520 |
| Format | 16 x 24 |
| Couverture | Relié |
| Poids | 878g |
| Intérieur | Noir et Blanc |
| EAN13 | 9780471420286 |
| ISBN13 | 978-0-471-42028-6 |
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