Table of contents

  1. Front Matter
    Pages I-XVIII
  2. Antonio Robles-Kelly, Cong Phuoc Huynh
    Pages 1-7
  3. Antonio Robles-Kelly, Cong Phuoc Huynh
    Pages 9-15
  4. Antonio Robles-Kelly, Cong Phuoc Huynh
    Pages 17-35
  5. Antonio Robles-Kelly, Cong Phuoc Huynh
    Pages 37-51
  6. Antonio Robles-Kelly, Cong Phuoc Huynh
    Pages 53-61
  7. Antonio Robles-Kelly, Cong Phuoc Huynh
    Pages 63-87
  8. Antonio Robles-Kelly, Cong Phuoc Huynh
    Pages 89-140
  9. Antonio Robles-Kelly, Cong Phuoc Huynh
    Pages 141-174
  10. Antonio Robles-Kelly, Cong Phuoc Huynh
    Pages 175-207
  11. Antonio Robles-Kelly, Cong Phuoc Huynh
    Pages 209-239
  12. Antonio Robles-Kelly, Cong Phuoc Huynh
    Pages 241-263
  13. Back Matter
    Pages 265-269

About this book

Introduction

In contrast with trichromatic image sensors, imaging spectroscopy can capture the properties of the materials in a scene. This implies that scene analysis using imaging spectroscopy has the capacity to robustly encode material signatures, infer object composition and recover photometric parameters.

This landmark text/reference presents a detailed analysis of spectral imaging, describing how it can be used in elegant and efficient ways for the purposes of material identification, object recognition and scene understanding. The opportunities and challenges of combining spatial and spectral information are explored in depth, as are a wide range of applications from surveillance and computational photography, to biosecurity and resource exploration.

Topics and features:

  • Discusses spectral image acquisition by hyperspectral cameras, and the process of spectral image formation
  • Examines models of surface reflectance, the recovery of photometric invariants, and the estimation of the illuminant power spectrum from spectral imagery
  • Describes spectrum representations for the interpolation of reflectance and radiance values, and the classification of spectra
  • Reviews the use of imaging spectroscopy for material identification
  • Explores the recovery of reflection geometry from image reflectance
  • Investigates spectro-polarimetric imagery, and the recovery of object shape and material properties using polarimetric images captured from a single view

An essential resource for researchers and graduate students of computer vision and pattern recognition, this comprehensive introduction to imaging spectroscopy for scene analysis will also be of great use to practitioners interested in shape analysis employing polarimetric imaging, and material recognition and classification using hyperspectral or multispectral data.

Keywords

Computer Vision Imaging Spectroscopy Pattern Recognition Scene Analysis Spectral Imaging

Authors and affiliations

  • Antonio Robles-Kelly
    • 1
  • Cong Phuoc Huynh
    • 2
  1. 1.National ICT AustraliaCanberraAustralia
  2. 2.National ICT AustraliaCanberraAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-4652-0
  • Copyright Information Springer-Verlag London 2013
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-4471-4651-3
  • Online ISBN 978-1-4471-4652-0
  • Series Print ISSN 2191-6586
  • Series Online ISSN 2191-6594
  • About this book