Overview
- Provides a comprehensive review of the state of the art in hyperspectral image analysis
- Presents perspectives from experts who are pioneers in a broad range of signal processing and machine learning fields related to hyperspectral imaging and remote sensing
- Is suitable both as a reference book and as a textbook for advanced graduate courses on multi-dimensional image processing
Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)
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Table of contents (15 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas ofimage analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.
Editors and Affiliations
About the editors
Dr. Saurabh Prasad is an Associate Professor at the Department of Electrical and Computer Engineering at the University of Houston, TX, USA.
Dr. Jocelyn Chanussot is a Professor in the Signal and Images Department at Grenoble Institute of Technology, France.
Bibliographic Information
Book Title: Hyperspectral Image Analysis
Book Subtitle: Advances in Machine Learning and Signal Processing
Editors: Saurabh Prasad, Jocelyn Chanussot
Series Title: Advances in Computer Vision and Pattern Recognition
DOI: https://doi.org/10.1007/978-3-030-38617-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-38616-0Published: 28 April 2020
Softcover ISBN: 978-3-030-38619-1Published: 29 April 2021
eBook ISBN: 978-3-030-38617-7Published: 27 April 2020
Series ISSN: 2191-6586
Series E-ISSN: 2191-6594
Edition Number: 1
Number of Pages: VI, 466
Number of Illustrations: 26 b/w illustrations, 144 illustrations in colour
Topics: Image Processing and Computer Vision, Artificial Intelligence, Remote Sensing/Photogrammetry, Signal, Image and Speech Processing