Advanced Image Processing Techniques for Remotely Sensed Hyperspectral DataOver 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. |
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 |
Other editions - View all
Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data Pramod K. Varshney,Manoj K. Arora No preview available - 2014 |
Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data Pramod K. Varshney,Manoj K. Arora No preview available - 2010 |
Common terms and phrases
applications approach artifact patterns AVIRIS based registration canbe Chen classification accuracy classification algorithm computed configuration convergence corresponding dataset dimensional distribution empirical risk endmembers entropy error matrix feature extraction Foody fusion fuzzy Gaussian Geoscience and Remote Gibbs global global optimum HyMap hyperplane hyperspectral data hyperspectral image Hyvärinen ICAFE IEEE Transactions image registration independent component analysis intensity values interpolation inthe Inthis iterative joint entropy joint histogram estimation kernel function Kmeans kurtosis Lagrange multipliers land cover linear separating hyperplane maximum method minimization mixture model MRF model multiclass multisensor multispectral multitemporal mutual information neural network nonGaussian numberof observed obtained ofthe optimum order GPVE Overall Accuracy parameters performance pixel pixel vector PVI algorithm random vector reference image registration consistency registration function Remote Sensing remote sensing images sensors similarity measure spatial resolution SPCA spectral bands statistical support vector machines tothe transformation update Vapnik variance Varshney VCdimension zero