Multi-Sensor Image Fusion and Its Applications

Combining information from multiple sources, image fusion provides a more accurate description of a scene than any one of the individual source images alone. Using multiple modalities increases the reliability and overall performance compared to single-sensor imaging systems, as the various sensors provide complementary information about the scene. This text explores both the theoretical and applicative aspects of image fusion, illustrating its uses in concealed weapon detection, surveillance, medical diagnosis, and remote sensing, to name only a few. The authors discuss the progress of research into image fusion and highlight the way to solve practical problems using the technique.

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.

PrefaceAN OVERVIEW OF IMAGE FUSIONRick S. Blum, Zhiyun Xue, and Zhong ZhangMUTUAL INFORMATION BASED IMAGE REGISTRATION WITH APPLICATION TO 3D MEDICAL BRAIN IMAGERYHua-Mei Chen and Pramod K. VarshneySTUDIES IN REGISTRATION AND FUSION OF RETINAL IMAGESFrance Laliberté and Langis GagnonNONRIGID MR/US REGISTRATION FOR TRACKING BRAIN DEFORMATIONSXavier Pennec, Nicholas Ayache, Alexis Roche, and Pascal CathierMULTISENSOR DATA INVERSION AND FUSION BASED ON SHARED IMAGE STRUCTURERobert A. Weisenseel, William C. Karl, and Raymond C. ChanENTROPIC GRAPHS FOR REGISTRATIONHuzefa Neemuchwala and Alfred HeroFUSION OF IMAGES FROM DIFFERENT ELECTRO-OPTICAL SENSING MODALITIES FOR SURVEILLANCE AND NAVIGATION TASKSAlexander ToetA STATISTICAL SIGNAL PROCESSING APPROACH TO IMAGE FUSION USING HIDDEN MARKOV MODELSJinzhong Yang and Rick S. BlumMULTIMODAL HUMAN RECOGNITION SYSTEMSArun Ross and Anil K. JainCHANGE DETECTION/INTERPRETATION WITH EVIDENTIAL FUSION OF CONTEXTUAL ATTRIBUTES: APPLICATIONS TO MULTIPASS RADARSAT-1 DATAAlexandre Jouan, Yannick Allard, and Yves MarcozMULTISENSOR REGISTRATION FOR EARTH REMOTELY SENSED IMAGERYJacqueline Le Moigne and Roger EastmanSYSTEM AND MODEL-BASED APPROACHES TO DATA FUSION FOR NDE APPLICATIONSLalita Udpa, Satish Udpa, and Antonello TamburrinoFUSION OF MULTIMODAL NDI IMAGES FOR AIRCRAFT CORROSION DETECTION AND QUANTIFICATIONZheng Liu, David S. Forsyth, and Jerzy P. KomorowskiFUSION OF BLURRED IMAGESFilip ?Sroubek and Jan FlusserGAZE-CONTINGENT MULTIMODALITY DISPLAYS FOR VISUAL INFORMATION FUSION: SYSTEMS AND APPLICATIONSStavri Nikolov, Michael Jones, Iain Gilchrist, David Bull, and Nishan CanagarajahSTRUCTURAL AND INFORMATION THEORETIC APPROACHES TO IMAGE QUALITY ASSESSMENTKalpana Seshadrinathan, Hamid R. Sheikh, Alan C. Bovik, and Zhou Wang

Rick S. Blum, Zheng Liu