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Detection of Man-made Objects in Satellite Images
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-5698-5983
1997 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In this report, the principles of man-made object detection in satellite images is investigated. An overview of terminology and of how the detection problem is usually solved today is given. A three level system to solve the detection problem is proposed. The main branches of this system handle road, and city detection respectively. To achieve data source flexibility, the Logical Sensor notion is used to model the low level system components. Three Logical Sensors have been implemented and tested on Landsat TM and SPOT XS scenes. These are: BDT (Background Discriminant Transformation) to construct a man-made object property field; Local-orientation for texture estimation and road tracking; Texture estimation using local variance and variance of local orientation. A gradient magnitude measure for road seed generation has also been tested.

Place, publisher, year, edition, pages
1997. , 93 p.
Series
LiTH-ISY-Ex, 1852
Keyword [en]
Remote sensing, computer vision, logical sensors, road detection, man-made objects, spectral signature, local variance, quadrature filter
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-54356ISRN: n/aOAI: oai:DiVA.org:liu-54356DiVA: diva2:303014
Presentation
(English)
Uppsok
Technology
Available from: 2010-03-10 Created: 2010-03-10 Last updated: 2015-12-10Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
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