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A comparative evaluation of spectral reflectance representations for spectrum reconstruction, interpolation and classification

conference contribution
posted on 2013-01-01, 00:00 authored by Cong Phuoc Huynh, Antonio Robles-KellyAntonio Robles-Kelly
Due to the high dimensionality of spectral data, spectrum representation techniques have often concentrated on modelling the spectra as a linear combination of a small basis set. Here, we focus on the evaluation of a B-Spline representation, a Gaussian mixture model, PCA and wavelets when applied to represent real-world spectrometer and spectral image data. These representations are important since they open up the possibility of reducing densely sampled spectra to a compact form for spectrum reconstruction, interpolation and classification. In particular, we shall perform an evaluation of these representations for the above tasks on two datasets consisting of reflectance spectra and hyperspectral images.

History

Pagination

328-335

Location

Portland, Or.

Start date

2013-06-23

End date

2013-06-28

ISBN-13

978-0-7695-4990-3

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2013, IEEE

Title of proceedings

CVPRW 2013 : Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops

Event

IEEE Computer Society. Conference (2013 : Portland, Or.)

Publisher

Institute of Electrical and Electronics Engineers

Place of publication

Piscataway, N.J.

Series

IEEE Computer Society Conference

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