Hyperspectral Imaging Remote Sensing: Physics, Sensors, and Algorithms

Hyperspectral Imaging Remote Sensing: Physics, Sensors, and Algorithms

Cambridge | English | November 2016 | ISBN-10: 1107083664 | 706 Pages | PDF | 19.37 mb


Dimitris G. Manolakis, Massachusetts Institute of Technology, Lincoln Laboratory, Ronald B. Lockwood, Massachusetts Institute of Technology, Lincoln Laboratory, Thomas W. Cooley

Book description
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.

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

Subjects
Engineering, Remote Sensing and Gis, Earth and Environmental Sciences, Communications and Signal Processing

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