Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

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Springer Science & Business Media, Mar 9, 2013 - Science - 323 pages
Over the last fifty years, a large number of spaceborne and airborne sensors have been employed to gather information regarding the earth's surface and environment. As sensor technology continues to advance, remote sensing data with improved temporal, spectral, and spatial resolution is becoming more readily available. This widespread availability of enormous amounts of data has necessitated the development of efficient data processing techniques for a wide variety of applications. In particular, great strides have been made in the development of digital image processing techniques for remote sensing data. The goal has been efficient handling of vast amounts of data, fusion of data from diverse sensors, classification for image interpretation, and development of user-friendly products that allow rich visualization. This book presents some new algorithms that have been developed for high dimensional datasets, such as multispectral and hyperspectral imagery. The contents of the book are based primarily on research carried out by some members and alumni of the Sensor Fusion Laboratory at Syracuse University.
 

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Contents

Contents
1954
Overview of Image Processing
2012
A Similarity Measure for Intensity Based
2-3
Algorithm
2-6
Algorithm ICAFE
2-8
AnMRF ModelBased Approachfor
2-27
Hyperspectral Data
2-39
1 Introduction
3-29
Independent Component Analysis
3-57
Support Vector Machines
3-60
Theory
3-174
SpatialResolution
9-7
Classification of Multi
9-12
and Decision TreeStructure 5 4 4 Multiclass ObjectiveFunction 5 5 Optimization Methods
11-18
Theory
11-21
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