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Imaging Spectroscopy for Scene Analysis pp 89–140Cite as

Spectrum Representation

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Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

In this chapter, we provide an overview of spectrum representation methods. Along these lines, we review compact representations of the spectrum commonly used in the literature. These representations include those that view the spectra as a mixture, those that represent the spectra using a spline and subspace projection methods. We then focus on the representation of the spectra based upon log-linearity and heavy-tailed probability distributions. This permits the use of harmonic analysis so as to understand affine invariance and band correlation in spectral imaging. We finish the chapter by elaborating upon the automatic recovery of absorptions making use of methods such as fingerprint, derivative analysis, unimodal segmentation, etc. we also provide a complexity analysis and comment on absorption representation.

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Notes

  1. 1.

    http://speclab.cr.usgs.gov/spectral-lib.html.

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Authors and Affiliations

  1. National ICT Australia, Canberra, ACT, Australia

    Antonio Robles-Kelly & Cong Phuoc Huynh

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  1. Antonio Robles-Kelly
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  2. Cong Phuoc Huynh
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Robles-Kelly, A., Huynh, C.P. (2013). Spectrum Representation. In: Imaging Spectroscopy for Scene Analysis. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-4652-0_7

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  • DOI: https://doi.org/10.1007/978-1-4471-4652-0_7

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