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Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data /

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The main objective of this book is to apprise the reader of the use of a number of tools and techniques for a variety of image processing tasks, namely Independent Component Analysis (ICA), Mutual Information (MI), Markov Random Field (MRF) Models and Support Vector Machines (SVM). Typical applicati...

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Bibliographic Details
Main Author: Varshney, Pramod K.
Corporate Author: SpringerLink (Online service)
Other Authors: Arora, Manoj K.
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2004.
Subjects:
Geography.
Geographic information systems.
Computer engineering.
Environmental toxicology.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Hyperspectral Sensors and Applications
  • Overview of Image Processing
  • Mutual Information: A Similarity Measure for Intensity Based Image Registration
  • Independent Component Analysis
  • Support Vector Machines
  • Markov Random Field Models
  • Applications: MI Based Registration of Multi-Sensor and Multi-Temporal Images
  • Feature Extraction from Hyperspectral Data Using ICA
  • Hyperspectral Classification using ICA Based Mixture Model
  • Support Vector Machines for Classification of Multi- and Hyperspectral Data
  • An MRF Model Based Approach for Sub-pixel Mapping from Hyperspectral Data
  • Image Change Detection and Fusion Using MRF Models.