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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-KellyDue 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
Event
IEEE Computer Society. Conference (2013 : Portland, Or.)Series
IEEE Computer Society ConferencePagination
328 - 335Publisher
Institute of Electrical and Electronics EngineersLocation
Portland, Or.Place of publication
Piscataway, N.J.Publisher DOI
Start date
2013-06-23End date
2013-06-28ISBN-13
978-0-7695-4990-3Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2013, IEEETitle of proceedings
CVPRW 2013 : Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition WorkshopsUsage metrics
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