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.
Table of Content
An Overview of Image Fusion
Mutual Information Based Image Registration with Application to 3D Medical Brain Imagery
Studies on 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 from 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
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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