Outlier and target detection in aerial hyperspectral imagery

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Abstract

The use of aerial hyperspectral imagery for the purpose of remote sensing is a rapidly growing research area. Currently, targets are generally detected by looking for distinct spectral features of the objects under surveillance. This work aims to develop improved target detection methods, using a two-stage approach, firstly by development of a physics-based atmospheric correction algorithm to convert
radiance into reflectance hyperspectral image data and secondly by use of improved spectral unmixing techniques.
Original languageEnglish
Title of host publicationProceedings of HSI 2014, 15-16th October 2014
Subtitle of host publicationHyperspectral Imaging and Applications Conference
Place of PublicationEngland
Number of pages2
Publication statusPublished - Oct 2014
EventHyperspectral Imaging and Applications Conference (HSI 2014) - Ricoh Arena, Coventry, United Kingdom
Duration: 15 Oct 201416 Oct 2014

Conference

ConferenceHyperspectral Imaging and Applications Conference (HSI 2014)
CountryUnited Kingdom
CityCoventry
Period15/10/1416/10/14

Keywords

  • hyperspectral imaging
  • target detection
  • remote sensing
  • spectral unmixing

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  • Cite this

    Young, A., Killey, A., Marshall, S., & Gray, A. (2014). Outlier and target detection in aerial hyperspectral imagery. In Proceedings of HSI 2014, 15-16th October 2014: Hyperspectral Imaging and Applications Conference England.