Latest revision as of 13:39, 21 January 2021

Abstract

Over the past decades, considerable progress had been made in developing automatic image interpretation tools for remote sensing. There is, however, still a gap between the requirements of applications and system capabilities. Interpretation of noisy aerial images, especially in low resolution, is still difficult. We present a system aimed at detecting faint linear structures, such as pipelines and access roads, in aerial images. We introduce an orientation-weighted Hough transform for the detection of line segments and a Markov Random Field model for combining line segments into linear structures. Empirical results show that the proposed method yields good detection performance.

Original document

The different versions of the original document can be found in:

• http://www.cs.ualberta.ca/~wfb/publications/C-2009-ICIAR.pdf

• http://link.springer.com/content/pdf/10.1007/978-3-642-02611-9_88,

http://dx.doi.org/10.1007/978-3-642-02611-9_88 under the license http://www.springer.com/tdm

• https://webdocs.cs.ualberta.ca/~wfb/ammi/publications/C-2009-ICIAR.pdf,

http://core.ac.uk/display/21201695,

https://dblp.uni-trier.de/db/conf/iciar/iciar2009.html#GaoB09,

https://link.springer.com/chapter/10.1007/978-3-642-02611-9_88,

https://www.scipedia.com/public/Gao_Bischof_2009a,

https://doi.org/10.1007/978-3-642-02611-9_88,

https://dl.acm.org/citation.cfm?id=1577691,

https://rd.springer.com/chapter/10.1007/978-3-642-02611-9_88,

https://academic.microsoft.com/#/detail/1552864862