Detection of linear structures in remote sensed images


== 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://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://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 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 https://webdocs.cs.ualberta.ca/~wfb/ammi/publications/C-2009-ICIAR.pdf],
: [http://core.ac.uk/display/21201695 http://core.ac.uk/display/21201695],
: [https://dblp.uni-trier.de/db/conf/iciar/iciar2009.html#GaoB09 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://link.springer.com/chapter/10.1007/978-3-642-02611-9_88],
: [https://www.scipedia.com/public/Gao_Bischof_2009a https://www.scipedia.com/public/Gao_Bischof_2009a],
: [https://doi.org/10.1007/978-3-642-02611-9_88 https://doi.org/10.1007/978-3-642-02611-9_88],
: [https://dl.acm.org/citation.cfm?id=1577691 https://dl.acm.org/citation.cfm?id=1577691],
: [https://rd.springer.com/chapter/10.1007/978-3-642-02611-9_88 https://rd.springer.com/chapter/10.1007/978-3-642-02611-9_88],
: [https://academic.microsoft.com/#/detail/1552864862 https://academic.microsoft.com/#/detail/1552864862]