An analysis of spectral metrics for hyperspectral image processing

Research output: Contribution to conferencePaperResearchpeer-review

10 Citations (Scopus)

Abstract

This paper investigates the efficiency of spectral metrics when used in spectral screening of hyperspectral imagery. Spectral screening is the technique of selecting from the data a subset of spectra such that any two spectra in the subset are dissimilar and, for any spectra in the original image cube, there is a similar spectra in the subset. The method can use various spectral metrics to characterize the similarity and can be seen as a data reduction step if the resulting subset is used in further computations instead of the full data. The investigation has focused on the comparison between spectral angle and spectral correlation angle in terms of efficiency of the results and speedup obtained as well as in empirically identifying the best distance threshold to be used when reducing the data. The techniques were tested on Hyperion imagery when using PCA and show promising speedup.

Original languageEnglish
Pages3233-3236
Number of pages4
StatePublished - 1 Dec 2004
Event2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 - Anchorage, AK, United States
Duration: 20 Sep 200424 Sep 2004

Other

Other2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004
CountryUnited States
CityAnchorage, AK
Period20/09/0424/09/04

Fingerprint

image processing
Screening
Image processing
Set theory
Data reduction
imagery
Hyperion
analysis
screening

Keywords

  • Data reduction
  • Hyperspectral images
  • Spectral angle
  • Spectral correlation angle
  • Spectral metrics

Cite this

Robila, S. (2004). An analysis of spectral metrics for hyperspectral image processing. 3233-3236. Paper presented at 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004, Anchorage, AK, United States.
Robila, Stefan. / An analysis of spectral metrics for hyperspectral image processing. Paper presented at 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004, Anchorage, AK, United States.4 p.
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Robila, S 2004, 'An analysis of spectral metrics for hyperspectral image processing' Paper presented at 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004, Anchorage, AK, United States, 20/09/04 - 24/09/04, pp. 3233-3236.

An analysis of spectral metrics for hyperspectral image processing. / Robila, Stefan.

2004. 3233-3236 Paper presented at 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004, Anchorage, AK, United States.

Research output: Contribution to conferencePaperResearchpeer-review

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AB - This paper investigates the efficiency of spectral metrics when used in spectral screening of hyperspectral imagery. Spectral screening is the technique of selecting from the data a subset of spectra such that any two spectra in the subset are dissimilar and, for any spectra in the original image cube, there is a similar spectra in the subset. The method can use various spectral metrics to characterize the similarity and can be seen as a data reduction step if the resulting subset is used in further computations instead of the full data. The investigation has focused on the comparison between spectral angle and spectral correlation angle in terms of efficiency of the results and speedup obtained as well as in empirically identifying the best distance threshold to be used when reducing the data. The techniques were tested on Hyperion imagery when using PCA and show promising speedup.

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Robila S. An analysis of spectral metrics for hyperspectral image processing. 2004. Paper presented at 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004, Anchorage, AK, United States.