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Multi-Sensor Image Fusion and Its Applications

Edited By

Rick S. Blum

,

Zheng Liu




ISBN 9780849334177
Published July 28, 2005 by CRC Press
528 Pages 49 Color & 204 B/W Illustrations

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Book Description

Taking another lesson from nature, the latest advances in image processing technology seek to combine image data from several diverse types of sensors in order to obtain a more accurate view of the scene: very much the same as we rely on our five senses. Multi-Sensor Image Fusion and Its Applications is the first text dedicated to the theory and practice of the registration and fusion of image data, covering such approaches as statistical methods, color-related techniques, model-based methods, and visual information display strategies.

After a review of state-of-the-art image fusion techniques, the book provides an overview of fusion algorithms and fusion performance evaluation. The following chapters explore recent progress and practical applications of the proposed techniques to solving problems in such areas as medical diagnosis, surveillance and biometric systems, remote sensing, nondestructive evaluation, blurred image restoration, and image quality assessment. Recognized leaders from industry and academia contribute the chapters, reflecting the latest research trends and providing useful algorithms to aid implementation.

Supplying a 28-page full-color insert, Multi-Sensor Image Fusion and Its Applications clearly demonstrates the benefits and possibilities of this revolutionary development. It provides a solid knowledge base for applying these cutting-edge techniques to new challenges and creating future advances.

Table of Contents

An Overview of Image Fusion. Mutual Information Based Image Registration with Application to 3D Medical Brain Imagery. Studies in Registration and Fusion of Retinal Images. Nonrigid MR/US Registration for Tracking Brain Deformations. Multisensor Data Inversion and Fusion Based on Shared Image Structure. Entropic Graphs for Registration. Fusion of Images form Different Electro-Optical Sensing Modalities for Surveillance and Navigation Tasks. A Statistical Signal Processing Approach to Image Fusion Using Hidden Markov Models. Multimodal Human Recognition Systems. Change Detection/Interpretation with Evidential Fusion of Contextual Attributes: Applications to Multipass RADARSAT-1 Data. Multisensor Registration for Earth Remotely Sensed Imagery. System and Model-Based Approaches to Data Fusion for NDE Applications. Fusion of Multimodal NDI Images for Aircraft Corrosion Detection and Quantification. Fusion of Blurred Images. Gaze-Contingent Multimodality Displays for Visual Information Fusion: Systems and Applications. Structural and Information Theoretic Approaches to Image Quality Assessment.

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