Referenced Items are not available for this document.
A general processing framework for urban road network extraction in high-resolution synthetic aperture radar images is proposed. It is based on novel multiscale detection of street candidates, followed by optimization using a Markov random field description of the road network. The latter step, in the path of recent technical literature, is enriched by the inclusion of a priori knowledge about road junctions and the automatic choice of most of the involved parameters. Advantages over existing and previous extraction and optimization procedures are proved by comparison using data from different sensors and locations
Published in:
Geoscience and Remote Sensing, IEEE Transactions on
(Volume:44
,
Issue:
10
)
Date of Publication: Oct. 2006
- Page(s):
- 2962 - 2971
- ISSN :
- 0196-2892
- INSPEC Accession Number:
- 9116805
- Digital Object Identifier :
- 10.1109/TGRS.2006.877289
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 25 September 2006
- Issue Date :
- Oct. 2006
- Sponsored by :
- IEEE Geoscience and Remote Sensing Society
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