Computer Vision Beyond the Visible Spectrum

✍ Scribed by Michael Boshra, Bir Bhanu (auth.), Bir Bhanu PhD, Ioannis Pavlidis PhD (eds.)

• Publisher: Springer-Verlag London
• Year: 2005
• Tongue: English
• Leaves: 321
• Series: Advances in Pattern Recognition
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

A Theoretical Framework for Predicting Performance of Object Recognition....Pages 1-37
Methods for Improving the Performance of an SAR Recognition System....Pages 39-69
Three-Dimensional Laser Radar Recognition Approaches....Pages 71-114
Target Classification Using Adaptive Feature Extraction and Subspace Projection for Hyperspectral Imagery....Pages 115-140
Moving Object Detection and Compression in IR Sequences....Pages 141-165
Face Recognition in the Thermal Infrared....Pages 167-191
Cardiovascular MR Image Analysis....Pages 193-239
Visualization and Segmentation Techniques in 3D Ultrasound Images....Pages 241-269
Time-Frequency Analysis in Terahertz-Pulsed Imaging....Pages 271-311

✦ Subjects

Computer Graphics; Image Processing and Computer Vision; Pattern Recognition; Artificial Intelligence (incl. Robotics); Electronic and Computer Engineering; Neurosciences