Hyperspectral Imaging Remote Sensing: Physics, Sensors, and Algorithms

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.

Author: Dimitris G. Manolakis, Ronald B. Lockwood, Thomas W. Cooley
Publisher: Cambridge University Press
Published: 10/20/2016
Pages: 706
Binding Type: Hardcover
Weight: 3.30lbs
Size: 10.08h x 6.98w x 1.36d
ISBN: 9781107083660

About the Author
Cooley, Thomas: - Thomas 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.Cooley, Thomas: - Thomas 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.Manolakis, Dimitris G.: - 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.
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