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Hyperspectral Imaging - 1st Edition - ISBN: 9780444639776, 9780444639783

Hyperspectral Imaging, Volume 32

1st Edition

5.0 star rating 5 Reviews
Series Volume Editor: Jose Manuel Amigo
Paperback ISBN: 9780444639776
eBook ISBN: 9780444639783
Imprint: Elsevier
Published Date: 1st October 2019
Page Count: 800
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Table of Contents

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

2.1. Pre-processing of hyperspectral images. Spatial and spectral issues
2.2. Hyperspectral data compression
2.3. Pansharpening
2.4. Unsupervised pattern recognition methods
2.5. Multivariate Curve Resolution
2.6. Non Linear Spectral un-mixing
2.7. Variability of the endmembers in spectral unmixing
2.8. Regression models
2.9. Classical Least Squares for Detection and Classification
2.10. Supervised Classification Methods in Hyperspectral Imaging - Recent Advances
2.11. Fusion of Hyperspectral Imaging and LiDAR for Forest Monitoring
2.12. Hyperspectral time series analysis: Hyperspectral image data streams interpreted by modeling known and unknown variations
2.13. Statistical Biophysical Parameter Retrieval and Emulation with Gaussian Processes

3.1. Hyperspectral cameras adapted to the applications. How and when
3.2. Applications in Remote Sensing - Natural Landscapes
3.3. Applications in Remote Sensing - Anthropogenic activities
3.4. Vegetation and crops
3.5. Food and feed production
3.6. Hyperspectral Imaging for Food related Microbiology Applications
3.7. Hyperspectral Imaging in Medical Applications
3.8. Hyperspectral Imaging as a part of Pharmaceutical Product Design
3.9. Hyperspectral imaging for artworks investigation
3.10. Growing applications of hyperspectral and multispectral imaging


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


No. of pages:
© Elsevier 2020
1st October 2019
Paperback ISBN:
eBook ISBN:

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About the Series Volume Editor

Jose Manuel Amigo

José Manuel Amigo Rubio obtained his PhD (Cum Laude) in chemistry from the Autonomous University of Barcelona, Spain. Since 2007 and until 2019, he has been employed at the Department of Food Science of the University of Copenhagen, Denmark. In 2019 he was appointed Ikerbasque Research Professor at the University of the Basque Country, Spain. 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 130 publications and given more than 50 conferences at international meetings. He is currently editorial board member of Journal of Spectral Imaging, Chemometrics and Intelligent Laboratory Systems, and Analytica Chimica Acta. Moreover, he received the “2014 Chemometrics and Intelligent Laboratory Systems Award” and the “2019 Tomas Hirshfeld Award.”

Affiliations and Expertise

Ikerbasque Research Professor at the University of the Basque Country, Spain