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Image Fusion
~
Zhang, Xingchen.
Image Fusion
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Image Fusion/ by Gang Xiao, Durga Prasad Bavirisetti, Gang Liu, Xingchen Zhang.
Author:
Xiao, Gang.
other author:
Zhang, Xingchen.
Description:
XVIII, 404 p. 231 illus., 76 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Image Processing and Computer Vision. -
Online resource:
https://doi.org/10.1007/978-981-15-4867-3
ISBN:
9789811548673
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.
ISBN: 9789811548673
Standard No.: 10.1007/978-981-15-4867-3doiSubjects--Topical Terms:
670819
Image Processing and Computer Vision.
LC Class. No.: TA1630-1650
Dewey Class. No.: 006.6
Image Fusion
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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.
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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.
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