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Hyperspectral data processing : algorithm design and analysis / Chein-I Chang.

By: Contributor(s): Material type: TextTextPublication details: Hoboken, NJ : Wiley-Interscience, c2013.Description: xxvii, 1135 p. : ill. ; 27 cmISBN:
  • 9780471690566 (hardback)
Subject(s): DDC classification:
  • 621.3994 23 C456
LOC classification:
  • TA1637 .C4776 2013
Other classification:
  • TEC015000
Summary: "This book is intended to be a sequel from the author's other title with Kluwer "Hyperspectral Imaging: Techniques for Spectral Detection and Classification". It contains five major parts. Part I is new aspects of OSP including 7 chapters, OSP revisit, generalized OSP, FPGA designs for OSP and CEM, Kalman filter-based linear unmixing, least squares fully constrained linear mixture analysis, exploitation-based hyperspectral data compression and size estimation of supixel targets, Part II is interference rejection for linear unmixing composed of three chapters, signal-composed interference-annihilated theory, interference-annihilated noise-adjusted theory and information-processed matched filter theory; Part III is nonlinear non-literal techniques for linear unmixing consisting of 3 chapters, convex cone analysis, information theoretic criterion-based project pursuit and nonlinear mixing model analysis; Part IV is spectral coding comprising of three chapters, progressive spectral coding, spectral binary coding and spectral coding for band selection; Part V is applications made up of two chapters, applications to magnetic resonance imaging and landmine detection"--
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Includes bibliographical references (p. 1052-1069) and index.

"This book is intended to be a sequel from the author's other title with Kluwer "Hyperspectral Imaging: Techniques for Spectral Detection and Classification". It contains five major parts. Part I is new aspects of OSP including 7 chapters, OSP revisit, generalized OSP, FPGA designs for OSP and CEM, Kalman filter-based linear unmixing, least squares fully constrained linear mixture analysis, exploitation-based hyperspectral data compression and size estimation of supixel targets, Part II is interference rejection for linear unmixing composed of three chapters, signal-composed interference-annihilated theory, interference-annihilated noise-adjusted theory and information-processed matched filter theory; Part III is nonlinear non-literal techniques for linear unmixing consisting of 3 chapters, convex cone analysis, information theoretic criterion-based project pursuit and nonlinear mixing model analysis; Part IV is spectral coding comprising of three chapters, progressive spectral coding, spectral binary coding and spectral coding for band selection; Part V is applications made up of two chapters, applications to magnetic resonance imaging and landmine detection"--

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