Spectral-Spatial Classification of Hyperspectral Remote Sensing Images.
This comprehensive new resource brings you up to date on recent developments in the classification of hyperspectral images using both spectral and spatial information, including advanced statistical approaches and methods. The inclusion of spatial information to traditional approaches for hyperspect...
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| Language: | English |
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Norwood :
Artech House,
2015.
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| Local Note: | ProQuest Ebook Central |
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| 100 | 1 | |a Benediktsson, Jon Atli. | |
| 245 | 1 | 0 | |a Spectral-Spatial Classification of Hyperspectral Remote Sensing Images. |
| 260 | |a Norwood : |b Artech House, |c 2015. | ||
| 300 | |a 1 online resource (277 pages) | ||
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| 505 | 0 | |a Spectral-Spatial Classification of Hyperspectral Remote Sensing Images; Contents; Foreword; Acknowledgments; Chapter 1 Introduction; 1.1 INTRODUCTION TO HYPERSPECTRAL IMAGING SYSTEMS; 1.2 HIGH-DIMENSIONAL DATA; 1.2.1 Geometrical and Statistical Properties of High DimensionalData and the Need for Feature Reduction; 1.2.2 Conventional Spectral Classifiers and the Importance of Considering Spatial Information; 1.3 SUMMARY; Chapter 2Classification Approaches; 2.1 CLASSIFICATION; 2.2 STATISTICAL CLASSIFICATION; 2.2.1 Support Vector Machines; 2.2.2 Neural Network Classifiers. | |
| 505 | 8 | |a 2.2.3 Decision Tree Classifiers2.3 MULTIPLE CLASSIFIERS; 2.3.1 Boosting; 2.3.2 Bagging; 2.3.3 Random Forest; 2.4 THE ECHO CLASSIFIER; 2.5 ESTIMATION OF CLASSIFICATION ERROR; 2.5.1 Confusion Matrix; 2.5.2 Average Accuracy (AA); 2.6 SUMMARY; Chapter 3Feature Reduction; 3.1 FEATURE EXTRACTION (FE); 3.1.1 Principal Component Analysis (PCA); 3.1.2 Independent Compone. | |
| 520 | |a This comprehensive new resource brings you up to date on recent developments in the classification of hyperspectral images using both spectral and spatial information, including advanced statistical approaches and methods. The inclusion of spatial information to traditional approaches for hyperspectral classification has been one of the most active and relevant innovative lines of research in remote sensing during recent years. This book gives you insight into several important challenges when performing hyperspectral image classification related to the imbalance between high dimensionality and limited availability of training samples, or the presence of mixed pixels in the data. This book also shows you how to integrate spatial and spectral information in order to take advantage of the benefits that both sources of information provide. | ||
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| 650 | 0 | |a Remote sensing. | |
| 650 | 0 | |a Multispectral imaging. | |
| 650 | 0 | |a Image processing |x Digital techniques. | |
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