Hyperspectral Imaging - 1st Edition - ISBN: 9780444639776

Hyperspectral Imaging, Volume 32

1st Edition

Series Volume Editors: Jose Manuel Amigo
Paperback ISBN: 9780444639776
Imprint: Elsevier
Published Date: 1st September 2019
Page Count: 450
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Table of Contents

Section 1. Introduction
1.1. Hyperspectral images. From remote sensing to bench top instruments. A general overview
1.2. Hyperspectral cameras. Types of hyperspectral cameras, radiations and sensors

Section 2. Algorithms and Methods
2.1. Pre-processing. Spatial and spectral issues
2.2. Hyperspectral data compression
2.3. Hyperspectral super-resolution
2.4. Pansharpening
2.5. Unsupervised pattern recognition methods
2.6. Multivariate curve resolution
2.7. Non-linear spectral un-mixing
2.8. Spectral un-mixing and variability of endmembers
2.9. Regression models
2.10. Classification
2.11. Mixing spatial with spectral signatures
2.12. Hyperspectral Image fusion
2.13. Hyperspectral video analysis
2.14. Advances in statistical biophysical parameter retrieval and model inversion

Section 3. Application Fields
3.1. Hyperspectral cameras adapted to the applications. How and when
3.2. Remote sensing
3.3. Vegetation and crops
3.4. Food and feed production
3.5. Biochemistry
3.6. Medical imaging
3.7. Pharmaceutical production
3.8. Artwork
3.9. Industrial hyperspectral imaging
3.10. Forensic sciences, and more

Section 4. Appendices
4.1. List of abbreviations
4.2. List of tables
4.3. List of figures


Hyperspectral Imaging, Volume 32, presents a comprehensive exploration of the different analytical methodologies applied on hyperspectral imaging and a state-of-the-art analysis of applications in different scientific and industrial areas. This book presents, for the first time, a comprehensive collection of the main multivariate algorithms used for hyperspectral image analysis in different fields of application. The benefits, drawbacks and suitability of each are fully discussed, along with examples of their application. Users will find state-of-the art information on the machinery for hyperspectral image acquisition, along with a critical assessment of the usage of hyperspectral imaging in diverse scientific fields.

Key Features

  • Provides a comprehensive roadmap of hyperspectral image analysis, with benefits and considerations for each method discussed
  • Covers state-of-the-art applications in different scientific fields
  • Discusses the implementation of hyperspectral devices in different environments


Scientists, academics, and graduate students in various disciplines working with hyperspectral images, including remote sensing, vegetation and crops, food and feed production, forensic sciences, biochemistry, medical imaging, pharmaceutical production, and art studies


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© Elsevier 2020
Paperback ISBN:

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About the Series Volume Editors

Jose Manuel Amigo Series Volume Editor

Dr. José Manuel Amigo obtained his PhD (Cum Laude) in Chemistry from the Autonomous University of Barcelona, Spain. Since 2007 he has been employed at the Department of Food Science of the University of Copenhagen, Denmark. Current research interests include hyperspectral and digital image analysis, and their implementation in Food and Forensic Sciences and Pharmaceutical production. He has authored more than 110 publications (80+ peer-reviewed papers, books, book chapters, proceedings, etc.) and given more than 40 conferences at international meetings. He has supervised or is currently supervising several Masters, Post Docs and PhD students. He is the current editor in-chief of the chemistry section of “MethodsX” and an editorial board member of “Chemometrics and Intelligent Laboratory Systems” and “Analytica Chimica Acta," among others. Moreover, he has received the “2014 Chemometrics and Intelligent Laboratory Systems Award."

Affiliations and Expertise

Department of Food Sciences, University of Copenhagen, Copenhagen, Denmark