Advantages and limitations of segmentation for point target detection in hyperspectral imagery

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Segmentation appears to be an attractive preprocessing state when performing point target detection in hyperspectral data. Nevertheless, the literature contains examples of both successful and unsuccessful segmentation. Using simulations and several new analytical tools, we propose to derive guidelines when segmentation would be useful and when it would be superfluous. A real dataset with parameters when segmentation is worthwhile and when not is given.

Original languageEnglish
Title of host publication2014 6th Workshop on Hyperspectral Image and Signal Processing
Subtitle of host publicationEvolution in Remote Sensing, WHISPERS 2014
PublisherIEEE Computer Society
ISBN (Electronic)9781467390125
DOIs
StatePublished - 28 Jun 2014
Event6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014 - Lausanne, Switzerland
Duration: 24 Jun 201427 Jun 2014

Publication series

NameWorkshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Volume2014-June
ISSN (Print)2158-6276

Conference

Conference6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014
Country/TerritorySwitzerland
CityLausanne
Period24/06/1427/06/14

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing

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