Hyperspectral Imaging Remote Sensing

Physics, Sensors, and Algorithms

Nonfiction, Science & Nature, Technology, Engineering, Science
Cover of the book Hyperspectral Imaging Remote Sensing by Dimitris G. Manolakis, Ronald B. Lockwood, Thomas W. Cooley, Cambridge University Press
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Author: Dimitris G. Manolakis, Ronald B. Lockwood, Thomas W. Cooley ISBN: 9781316028117
Publisher: Cambridge University Press Publication: October 20, 2016
Imprint: Cambridge University Press Language: English
Author: Dimitris G. Manolakis, Ronald B. Lockwood, Thomas W. Cooley
ISBN: 9781316028117
Publisher: Cambridge University Press
Publication: October 20, 2016
Imprint: Cambridge University Press
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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