Hyperspectral Imaging

Techniques for Spectral Detection and Classification

  • Chein-I Chang

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Introduction

    1. Chein-I Chang
      Pages 1-11
  3. Hyperspectral Measures

    1. Front Matter
      Pages 13-13
  4. Subpixel Detection

  5. Unconstrained Mixed Pixel Classification

  6. Constrained Mixed Pixel Classification

  7. Automatic Mixed Pixel Classification (AMPC)

About this book

Introduction

Hyperspectral Imaging: Techniques for Spectral Detection and Classification is an outgrowth of the research conducted over the years in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. It explores applications of statistical signal processing to hyperspectral imaging and further develops non-literal (spectral) techniques for subpixel detection and mixed pixel classification. This text is the first of its kind on the topic and can be considered a recipe book offering various techniques for hyperspectral data exploitation. In particular, some known techniques, such as OSP (Orthogonal Subspace Projection) and CEM (Constrained Energy Minimization) that were previously developed in the RSSIPL, are discussed in great detail. This book is self-contained and can serve as a valuable and useful reference for researchers in academia and practitioners in government and industry.

Keywords

classification detection digital elevation model image processing imaging remote sensing signal processing

Authors and affiliations

  • Chein-I Chang
    • 1
  1. 1.Remote Sensing Signal and Image Processing LaboratoryUniversity of Maryland, Baltimore CountyBaltimoreUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4419-9170-6
  • Copyright Information Kluwer Academic/Plenum Publishers, New York 2003
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-4820-7
  • Online ISBN 978-1-4419-9170-6
  • About this book