Computer Vision Beyond the Visible Spectrum

1. Front Matter

   Pages I-X

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2. A Theoretical Framework for Predicting Performance of Object Recognition

   • Michael Boshra, Bir Bhanu

   Pages 1-37

3. Methods for Improving the Performance of an SAR Recognition System

   • Bir Bhanu, Grinnell Jones III

   Pages 39-69

4. Three-Dimensional Laser Radar Recognition Approaches

   • Gregory Arnold, Timothy J. Klausutis, Kirk Sturtz

   Pages 71-114

5. Target Classification Using Adaptive Feature Extraction and Subspace Projection for Hyperspectral Imagery

   • Heesung Kwon, Sandor Z. Der, Nasser M. Nasrabadi

   Pages 115-140

6. Moving Object Detection and Compression in IR Sequences

   • Namrata Vaswani, Amit K Agrawal, Qinfen Zheng, Rama Chellappa

   Pages 141-165

7. Face Recognition in the Thermal Infrared

   • Lawrence B. Wolff, Diego A. Socolinsky, Christopher K. Eveland

   Pages 167-191

8. Cardiovascular MR Image Analysis

   • Milan Sonka, Daniel R. Thedens, Boudewijn P. F. Lelieveldt, Steven C. Mitchell, Rob J. van der Geest, Johan H. C. Reiber

   Pages 193-239

9. Visualization and Segmentation Techniques in 3D Ultrasound Images

   • Aaron Fenster, Mingyue Ding, Ning Hu, Hanif M. Ladak, Guokuan Li, Neale Cardinal et al.

   Pages 241-269

10. Time-Frequency Analysis in Terahertz-Pulsed Imaging

    • Elizabeth Berry, Roger D Boyle, Anthony J Fitzgerald, James W Handley

    Pages 271-311

11. Back Matter

    Pages 313-319

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Recently, there has been a dramatic increase in the use of sensors in the non-visible bands. As a result, there is a need for existing computer vision methods and algorithms to be adapted for use with non-visible sensors, or for the development of completely new methods and systems. Computer Vision Beyond the Visible Spectrum is the first book to bring together state-of-the-art work in this area. It presents new & pioneering research across the electromagnetic spectrum in the military, commercial, and medical domains. By providing a detailed examination of each of these areas, it focuses on the development of state-of-the-art algorithms and looks at how they can be used to solve existing & new challenges within computer vision. Essential reading for academics & industrial researchers working in the area of computer vision, image processing, and medical imaging, it will also be useful background reading for advanced undergraduate & postgraduate students.

• 3D
• Augmented Reality
• classification
• cognition
• computer
• computer vision
• image analysis
• image processing
• imaging
• object recognition
• performance
• proving
• radar
• ultrasound
• visualization

• Center for Research in Intelligent Systems, University of California at Riverside, USA

  Bir Bhanu

• Department of Computer Science, University of Houston, USA

  Ioannis Pavlidis

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