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Full Description
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.
Contents
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.