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Hyperspectral Imaging Remote Sensing Dimitris G. Manolakis

Hyperspectral Imaging Remote Sensing By Dimitris G. Manolakis

Hyperspectral Imaging Remote Sensing by Dimitris G. Manolakis

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Summary

Understand the principles, techniques and tools of imaging spectroscopy with this introductory guide providing comprehensive coverage of sensor design and calibration, atmospheric inversion and model techniques, and processing and exploitation algorithms. It explains how to apply algorithms to practical problems and interpret hyperspectral imaging data.

Hyperspectral Imaging Remote Sensing Summary

Hyperspectral Imaging Remote Sensing: Physics, Sensors, and Algorithms by Dimitris G. Manolakis

A practical and self-contained guide to the principles, techniques, models and tools of imaging spectroscopy. Bringing together material from essential physics and digital signal processing, it covers key topics such as sensor design and calibration, atmospheric inversion and model techniques, and processing and exploitation algorithms. Readers will learn how to apply the main algorithms to practical problems, how to choose the best algorithm for a particular application, and how to process and interpret hyperspectral imaging data. A wealth of additional materials accompany the book online, including example projects and data for students, and problem solutions and viewgraphs for instructors. This is an essential text for senior undergraduate and graduate students looking to learn the fundamentals of imaging spectroscopy, and an invaluable reference for scientists and engineers working in the field.

Hyperspectral Imaging Remote Sensing Reviews

'The authors have done a masterful job of integrating and presenting the diverse subjects that form the foundation of the field of hyperspectral imaging and applications. This comprehensive textbook will clearly become one of the standard references for all who wish to learn about both fundamentals and advanced applications in this important field.' Charles Bachmann, Rochester Institute of Technology, New York
'An extraordinarily comprehensive treatment of hyperspectral remote sensing by three of the field's noted authorities. An indispensable reference for those new to the field and for the seasoned professional.' Ronald G. Resmini, George Mason University, Virginia
'The authors have offered a comprehensive and up-to-date treatment of hyperspectral imaging modalities. A wide readership, including scientists and graduate students involved with spectral imaging modalities, could benefit from this book.' Axel Mainzer Koenig, Optics and Photonics

About Dimitris G. Manolakis

Dimitris G. Manolakis is a senior member of technical staff at the Lincoln Laboratory, Massachusetts Institute of Technology. He is the co-author of Applied Digital Signal Processing (Cambridge, 2011), and has taught at various institutions including Northeastern University, Boston, Boston College, Massachusetts, and Worcester Polytechnic Institute, Massachusetts. He is an IEEE Fellow, and in 2013 he received the IEEE Signal Processing Society Education Award. Ronald B. Lockwood is a member of technical staff at the Lincoln Laboratory, Massachusetts Institute of Technology. He previously worked at the Air Force Research Laboratory where he developed imaging spectrometers for both space-based and air-borne applications. He has also developed vicarious calibration techniques in collaboration with colleagues at the University of Arizona and the NASA Goddard Space Flight Center. Thomas W. Cooley is the Senior Scientist for Space Situational Awareness at the US Air Force Research Laboratory, and has made significant contributions to the fields of atmospheric compensation and spectral data analysis. He developed the ARTEMIS sensor program, which was successfully launched in 2009, and has published over 70 research papers.

Table of Contents

1. Introduction; 2. The remote sensing environment; 3. Spectral properties of materials; 4. Imaging spectrometers; 5. Imaging spectrometer characterization and data calibration; 6. Radiative transfer and atmospheric compensation; 7. Statistical models for spectral data; 8. Linear spectral transformations; 9. Spectral mixture analysis; 10. Signal detection theory; 11. Hyperspectral data exploitation; Appendix. Introduction to Gaussian optics.

Additional information

NPB9781107083660
9781107083660
1107083664
Hyperspectral Imaging Remote Sensing: Physics, Sensors, and Algorithms by Dimitris G. Manolakis
Dimitris G. Manolakis
New
Hardback
Cambridge University Press
2016-10-20
706
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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