Computer Vision Beyond the Visible Spectrum

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Bhanu, Bir (Επιμελητής έκδοσης), Pavlidis, Ioannis (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: London : Springer London, 2005.
• Σειρά: Advances in Pattern Recognition
• Θέματα: Computer science.; Neurosciences.; Artificial intelligence.; Computer graphics.; Image processing.; Pattern recognition.; Electrical engineering.; Computer Science.; Computer Graphics.; Image Processing and Computer Vision.; Pattern Recognition.; Artificial Intelligence (incl. Robotics).; Electrical Engineering.

 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. 

 A Theoretical Framework for Predicting Performance of Object Recognition -- Methods for Improving the Performance of an SAR Recognition System -- Three-Dimensional Laser Radar Recognition Approaches -- Target Classification Using Adaptive Feature Extraction and Subspace Projection for Hyperspectral Imagery -- Moving Object Detection and Compression in IR Sequences -- Face Recognition in the Thermal Infrared -- Cardiovascular MR Image Analysis -- Visualization and Segmentation Techniques in 3D Ultrasound Images -- Time-Frequency Analysis in Terahertz-Pulsed Imaging.