Image Fusion [electronic resource] /

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.

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.