© 2004

Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data


  • All available books only deal with basic image processing techniques; this book covers advanced techniques for image registration, feature extraction, image fusion and classification applications based on current research


Table of contents

  1. Front Matter
    Pages I-XV
  2. Introduction

    1. Pramod K. Varshney, Manoj K. Arora
      Pages 1-8
  3. General

    1. Front Matter
      Pages 9-9
    2. Richard Lucas, Aled Rowlands, Olaf Niemann, Ray Merton
      Pages 11-49
    3. Raghuveer M. Rao, Manoj K. Arora
      Pages 51-85
  4. Theory

    1. Front Matter
      Pages 87-87
    2. Stefan A. Robila
      Pages 109-132
    3. Mahesh Pal, Pakorn Watanachaturaporn
      Pages 133-157
    4. Teerasit Kasetkasem
      Pages 159-178
  5. Applications

    1. Front Matter
      Pages 179-179
    2. Hua-mei Chen, Pramod K. Varshney
      Pages 181-198
    3. Stefan A. Robila, Pramod K. Varshney
      Pages 199-216
    4. Manoj K. Arora, Pakorn Watanachaturaporn
      Pages 237-255
    5. Teerasit Kasetkasem, Manoj K. Arora, Pramod K. Varshney
      Pages 257-277
    6. Teerasit Kasetkasem, Pramod K. Varshney
      Pages 279-307
  6. Back Matter
    Pages 309-323

About this book


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.


Digital Image Processing GIS Hyperspectral Imaging Markov Random Field Pattern Recognition and Data Fusion Remote Sensing image processing image registration

Authors and affiliations

  1. 1.Department of Electrical Engineering and Computer Science, 121 Link HallSyracuse UniversitySyracuseUSA
  2. 2.Department of Civil EngineeringIndian Institute of Technology RoorkeeRoorkeeIndia

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