This book systematically discusses the basic concepts, theories, research and latest trends in image fusion. It focuses on three image fusion categories pixel, feature and decision presenting various applications, such as medical imaging, remote sensing, night vision, robotics and autonomous vehicles. Further, it introduces readers to a new category: edge-preserving-based image fusion, and provides an overview of image fusion based on machine learning and deep learning. As such, it is a valuable resource for graduate students and scientists in the field of digital image processing and information fusion.
Preface.- Author introduction.- Acknowledgement.- Part I: Image Fusion Theories.- Chapter 1: Introduction to Image Fusion.- Chapter 2: Pixel-level Image Fusion.- Chapter 3: Feature-level Image Fusion.- Chapter 4: Decision-level Image Fusion.- Chapter 5: Multi-sensor Dynamic Image Fusion.- Chapter 6: Objective Fusion Metrics.- Chapter 7: Image Fusion Based on Machine Learning and Deep Learning.- Part II: Experimental Examples.- Chapter 8: Example 1: Medical Image Fusion.- Chapter 9: Example 2: Night Vision image Fusion.- Chapter 10: Simulation Platform of Image Fusion.
Gang Xiao received his bachelors, masters and Ph. D degrees in 1998, 2001 and 2005 respectively. He is currently a Full Professor at the School of Aeronautics and Astronautics and the Director of the Advanced Avionics and Intelligent Information (AAII) Laboratory, Shanghai Jiao Tong University. He is senior member of the Chinese Aviation Society, member of Chinese Association of Automation and a member of the editorial board of the Information Fusion Journal. He was a visiting scholar at the University of California, San Diego (UCSD) in 2010 and Southern Illinois University Edwardsville (SIUE) in 2014. His current research inl³Ù
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