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Hyperspectral imaging remote sensing : physics, sensors, and algorithms / Dimitris G. Manolakis (Massachusetts Institute of Technology, Lincoln Laboratory), Ronald B. Lockwood (Massachusetts Institute of Technology, Lincoln Laboratory), Thomas W. Cooley (US Air Force Research Laboratory, Massachusetts).

By: Contributor(s): Material type: TextTextPublication details: Cambridge Cambridge University Press 2016Description: pages cmISBN:
  • 9781107083660
  • 1107083664
Subject(s): DDC classification:
  • 771 MAN.H
Online resources:
Contents:
The remote sensing environment -- Spectral properties of materials -- Imaging spectrometers -- Imaging spectrometer characterization and data calibration -- Radiative transfer and atmospheric compensation -- Statistical models for spectral data -- Linear spectral transformations -- Spectral mixture analysis -- Signal detection theory -- Hyperspectral data exploitation
Summary: "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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The remote sensing environment -- Spectral properties of materials -- Imaging spectrometers -- Imaging spectrometer characterization and data calibration -- Radiative transfer and atmospheric compensation -- Statistical models for spectral data -- Linear spectral transformations -- Spectral mixture analysis -- Signal detection theory -- Hyperspectral data exploitation

"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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