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An information measure of sensor performance and its relation to the ROC curve
Swedish Defence Research Agency (FOI), Linköping, Sweden.ORCID iD: 0000-0002-6763-5487
Swedish Defence Research Agency (FOI), Linköping, Sweden.
Swedish Defence Research Agency (FOI), Linköping, Sweden.
2010 (English)In: Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI / [ed] Sylvia S. Shen; Paul E. Lewis, SPIE - International Society for Optical Engineering, 2010, Art.nr. 7695-72- p.Conference paper, Published paper (Refereed)
Abstract [en]

The ROC curve is the most frequently used performance measure for detection methods and the underlying sensor configuration. Common problems are that the ROC curve does not present a single number that can be compared to other systems and that no discrimination between sensor performance and algorithm performance is done. To address the first problem, a number of measures are used in practice, like detection rate at a specific false alarm rate, or area-under-curve. For the second problem, we proposed in a previous paper1 an information theoretic method for measuring sensor performance. We now relate the method to the ROC curve, show that it is equivalent to selecting a certain point on the ROC curve, and that this point is easily determined. Our scope is hyperspectral data, studying discrimination between single pixels.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2010. Art.nr. 7695-72- p.
Series
Proceedings of SPIE, 7695
Keyword [en]
ROC, information theory, target detection, hyperspectral, sensor performance
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-120554DOI: 10.1117/12.851322OAI: oai:DiVA.org:liu-120554DiVA: diva2:846258
Conference
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, Orlando, Florida, USA, 5–8 April 2010
Available from: 2015-08-14 Created: 2015-08-14 Last updated: 2015-09-21Bibliographically approved

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Ahlberg, JörgenWadströmer, Niclas
Computer Vision and Robotics (Autonomous Systems)

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf