Evaluation of a statistical fusion of linear features in sar data

Karin Hedman, Stefan Hinz, Uwe Stilla

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

2 Zitate (Scopus)

Abstract

In this paper, we describe an extension of an automatic road extraction procedure developed for single SAR images towards multi-aspect SAR images. Extracted information from multi-aspect SAR images is not only redundant and complementary, in some cases even contradictory. Hence, multi-aspect SAR images require a careful selection within the fusion step. In this work, a fusion step based on probability theory is proposed. During fusion each extracted line primitive is assessed by means of Bayesian probability theory. The assessment is based on the attributes of the line primitive (i.e. length, straightness, etc), global context and sensor geometry. The fusion and its integration into the road extraction system are tested in a sub-urban SAR scene.

OriginalspracheEnglisch
Titel2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
SeitenIV467-IV470
Auflage1
DOIs
PublikationsstatusVeröffentlicht - 2008
Veranstaltung2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings - Boston, MA, USA/Vereinigte Staaten
Dauer: 6 Juli 200811 Juli 2008

Publikationsreihe

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Nummer1
Band4

Konferenz

Konferenz2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
Land/GebietUSA/Vereinigte Staaten
OrtBoston, MA
Zeitraum6/07/0811/07/08

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