Image Fusion
Xiao, Gang.
Image Fusion [electronic resource] / by Gang Xiao, Durga Prasad Bavirisetti, Gang Liu, Xingchen Zhang. - 1st ed. 2020. - XVIII, 404 p. 231 illus., 76 illus. in color. online 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.
9789811548673
10.1007/978-981-15-4867-3 doi
Computer vision.
Computer Vision.
TA1634
006.37
Image Fusion [electronic resource] / by Gang Xiao, Durga Prasad Bavirisetti, Gang Liu, Xingchen Zhang. - 1st ed. 2020. - XVIII, 404 p. 231 illus., 76 illus. in color. online 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.
9789811548673
10.1007/978-981-15-4867-3 doi
Computer vision.
Computer Vision.
TA1634
006.37