Remote Sensing Image Processing

✍ Scribed by Gustavo Camps-Valls, Devis Tuia, Luis Gómez-Chova, Sandra Jiménez, and Jesús Malo

• Publisher: Morgan & Claypool Publishers
• Year: 2012
• Tongue: English
• Leaves: 192
• Series: Synthesis Lectures on Image, Video, and Multimedia Processing 12
• Edition: 1
• Category: Library

✦ Synopsis

Earth observation is the field of science concerned with the problem of monitoring and modeling the processes on the Earth surface and their interaction with the atmosphere. The Earth is continuously monitored with advanced optical and radar sensors. The images are analyzed and processed to deliver useful products to individual users, agencies and public administrations. To deal with these problems, remote sensing image processing is nowadays a mature research area, and the techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, data coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This book covers some of the fields in a comprehensive way. Table of Contents: Remote Sensing from Earth Observation Satellites / The Statistics of Remote Sensing Images / Remote Sensing Feature Selection and Extraction / {Classification / Spectral Mixture Analysis / Estimation of Physical Parameters

✦ Table of Contents

Preface......Page 11
Acknowledgments......Page 15
Earth observation, spectroscopy and remote sensing......Page 17
Applications of remote sensing......Page 18
The remote sensing system......Page 19
The electromagnetic radiation......Page 20
Solar irradiance......Page 21
Earth atmosphere......Page 23
At-sensor radiance......Page 25
Spatial, spectral and temporal resolutions......Page 27
Optical sensors and platforms......Page 28
Remote sensing pointers......Page 30
Institutions......Page 31
Remote sensing companies......Page 32
Summary......Page 33
Introduction......Page 35
Second-order spatio-spectral regularities in hyperspectral images......Page 37
Separate spectral and spatial redundancy......Page 38
Joint spatio-spectral smoothness......Page 39
Application example to coding IASI data......Page 45
Higher order statistics......Page 48
Summary......Page 51
Introduction......Page 53
Filter methods......Page 54
Wrapper methods......Page 55
Feature Extraction......Page 57
Linear methods......Page 58
Nonlinear methods......Page 59
Feature extraction examples......Page 60
Physically Based Spectral Features......Page 63
Spectral feature extraction examples......Page 64
Co-occurrence textural features......Page 66
Morphological filters......Page 67
Spatial transforms......Page 69
Spatial feature extraction example......Page 71
Summary......Page 73
The classification problem: definitions......Page 75
Measures of accuracy......Page 77
Supervised methods......Page 79
Unsupervised methods......Page 80
A supervised classification example......Page 81
Change detection......Page 83
Unsupervised change detection......Page 84
Supervised change detection......Page 85
Detection of anomalies and targets......Page 87
Anomaly detection......Page 88
Target detection......Page 89
A target detection example......Page 90
Semisupervised learning......Page 92
Active learning......Page 93
Domain adaptation......Page 95
Summary......Page 98
Spectral unmixing steps......Page 99
A survey of applications......Page 100
Linear and nonlinear mixing models......Page 102
The linear mixing model......Page 104
Estimation of the number of endmembers......Page 105
A comparative analysis of signal subspace algorithms......Page 106
Endmember extraction......Page 107
Extraction techniques......Page 108
A comparative analysis of endmember extraction algorithms......Page 109
Linear approaches......Page 112
Nonlinear inversion......Page 113
Summary......Page 115
Introduction and principles......Page 117
Forward and inverse modeling......Page 118
Taxonomy of methods and outline......Page 119
Land inversion models......Page 120
Ocean inversion models......Page 123
Atmosphere inversion models......Page 126
Physical inversion techniques......Page 127
Optimization inversion methods......Page 128
Genetic algorithms......Page 129
Hybrid inversion methods......Page 130
Neural networks......Page 131
Land surface biophysical parameter estimation......Page 132
Optical oceanic parameter estimation......Page 134
Model inversion of atmospheric sounding data......Page 136
Summary......Page 137
Bibliography......Page 139
Author Biographies......Page 187
Index......Page 189