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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. | 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. | ||
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* [http://www.cs.ualberta.ca/~wfb/publications/C-2009-ICIAR.pdf http://www.cs.ualberta.ca/~wfb/publications/C-2009-ICIAR.pdf] | * [http://www.cs.ualberta.ca/~wfb/publications/C-2009-ICIAR.pdf http://www.cs.ualberta.ca/~wfb/publications/C-2009-ICIAR.pdf] | ||
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| + | * [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 | ||
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| + | * [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] | ||
Latest revision as of 14:39, 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://dx.doi.org/10.1007/978-3-642-02611-9_88 under the license http://www.springer.com/tdm
- 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
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Document information
Published on 01/01/2009
Volume 2009, 2009
DOI: 10.1007/978-3-642-02611-9_88
Licence: CC BY-NC-SA license
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