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Extraction of DTM from Satellite Images Using Neural Networks
Linköping University, Department of Electrical Engineering, Computer Vision.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This thesis presents a way to generate a Digital Terrain Model (dtm) from a Digital Surface Model (dsm) and multi spectral images (including the Near Infrared (nir) color band). An Artificial Neural Network (ann) is used to pre-classify the dsm and multi spectral images. This in turn is used to filter the dsm to a dtm. The use of an ann as a classifier provided good results. Additionally, the addition of the nir color band resulted in an improvement of the accuracy of the classifier. Using the classifier, a dtm was easily extracted without removing natural edges or height variations in the forests and cities. These challenges are handled with great satisfaction as compared to earlier methods.

Place, publisher, year, edition, pages
2016. , p. 70
Keywords [en]
DTM, DSM, classification, neural networks, satellite images
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-133337ISRN: LiTH-ISY-EX--16/5017--SEOAI: oai:DiVA.org:liu-133337DiVA, id: diva2:1058430
External cooperation
Vricon Systems AB
Subject / course
Computer Vision Laboratory
Presentation
2016-12-20, Transformen, Linköpings Universitet, Linköping, 15:15 (Swedish)
Supervisors
Examiners
Available from: 2016-12-21 Created: 2016-12-21 Last updated: 2016-12-21Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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