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LINE STRUCTURE-BASED TRAINING DATA EXTRACTION FOR BUILDING CLASSIFICATION OF HIGH RESOLUTION SATELLITE IMAGES

Yeom, Junho, Kim, Yongil

First published: 2016-06-28https://doi.org/10.5593/sgem2016/b22/s10.120View metrics

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Title
LINE STRUCTURE-BASED TRAINING DATA EXTRACTION FOR BUILDING CLASSIFICATION OF HIGH RESOLUTION SATELLITE IMAGES
Authors
Yeom, Junho, Kim, Yongil
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 16th International Multidisciplinary Scientific GeoConference SGEM2016, Informatics, Geoinformatics and Remote Sensing
Publisher
Stef92 Technology
Year
2016
Pages
939-946
ISSN
1314-2704
ISBN
978-619-7105-59-9
Language
en
Publication type
Conference Paper
References26

  1. Aytekin Ö., Erener A., Ulusoy İ., and Düzgün Ş., Unsupervised building detection in complex urban environments from multispectral satellite imagery, International Journal of Remote Sensing, United Kingdom, vol. 33/issue 7, pp 2152–2177, 2012.

  2. Lefèvre S., Weber J., and Sheeren D., Automatic building extraction in VHR images using advanced morphological operators, IEEE 2007 Urban Remote Sensing Joint Event, France, pp 1–5, 2007.

  3. Li G., Wan Y., and Chen C., Automatic building extraction based on region growing, mutual information match and snake model, Information Computing and Applications, China, pp 476–483, 2010.

  4. Huang X., and Zhang L., Morphological building/shadow index for building extraction from high-resolution imagery over urban areas, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, United States of America, vol. 5/issue 1, pp 161–172, 2012.

  5. Ok A. O., Senaras C., and Yuksel B., Automated detection of arbitrarily shaped buildings in complex environments from monocular VHR optical satellite imagery, IEEE Transactions on Geoscience and Remote Sensing , United States of America, vol. 51/issue 3, pp 1701–1717, 2013.

  6. Ahmadi S., Zoej M. J. V., Ebadi H., Moghaddam H. A., and Mohammadzadeh A., Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours, International Journal of Applied Earth Observation and Geoinformation, Netherlands, vol. 12/issue 3, pp 150–157, 2010.

  7. Senaras C., Ozay M., and Vural F. T. Y., Building detection with decision fusion , IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , United States of America, vol. 6/issue 3, pp 1295–1304, 2013.

  8. Dikmen M., and Halici U., A learning-based resegmentation method for extraction of buildings in satellite images, IEEE Geoscience and Remote Sensing Letters , United States of America, vol. 11/issue 12, pp 2150–2153, 2014.

  9. Jiang N., Zhang J. X., Li H. T., and Lin X. G., Semi-automatic building extraction from high resolution imagery based on segmentation, IEEE 2008 International Workshop on Earth Observation and Remote Sensing Applications, China, pp 1–5, 2008.

  10. Kim T., Lee T., and Kim K., Semiautomatic building line extraction from IKONOS Images through monoscopic line analysis, Photogrammetric Engineering and Remote Sensing, United States of America, vol. 72/issue 5, pp 541–549, 2006.

  11. Yeom J., and Kim Y., A regular grid -based Hough transform for the extraction of urban features using high -resolution satellite images , Remote Sensing Letters , United Kingdom, vol. 6/issue 5, pp 409–417, 2015.

  12. Vapnik V., Statistical learning theory, United States of America, 1998.

  13. Laben C. A., and Brower B. V., Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening, US Patent, United States of America, 2000. 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org

  14. Aytekin Ö., Erener A., Ulusoy İ., and Düzgün Ş., Unsupervised building detection in complex urban environments from multispectral satellite imagery, International Journal of Remote Sensing, United Kingdom, vol. 33/issue 7, pp 2152–2177, 2012.

  15. Lefèvre S., Weber J., and Sheeren D., Automatic building extraction in VHR images using advanced morphological operators, IEEE 2007 Urban Remote Sensing Joint Event, France, pp 1–5, 2007.

  16. Li G., Wan Y., and Chen C., Automatic building extraction based on region growing, mutual information match and snake model, Information Computing and Applications, China, pp 476–483, 2010.

  17. Huang X., and Zhang L., Morphological building/shadow index for building extraction from high-resolution imagery over urban areas, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, United States of America, vol. 5/issue 1, pp 161–172, 2012.

  18. Ok A. O., Senaras C., and Yuksel B., Automated detection of arbitrarily shaped buildings in complex environments from monocular VHR optical satellite imagery, IEEE Transactions on Geoscience and Remote Sensing , United States of America, vol. 51/issue 3, pp 1701–1717, 2013.

  19. Ahmadi S., Zoej M. J. V., Ebadi H., Moghaddam H. A., and Mohammadzadeh A., Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours, International Journal of Applied Earth Observation and Geoinformation, Netherlands, vol. 12/issue 3, pp 150–157, 2010.

  20. Senaras C., Ozay M., and Vural F. T. Y., Building detection with decision fusion , IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , United States of America, vol. 6/issue 3, pp 1295–1304, 2013.

  21. Dikmen M., and Halici U., A learning-based resegmentation method for extraction of buildings in satellite images, IEEE Geoscience and Remote Sensing Letters , United States of America, vol. 11/issue 12, pp 2150–2153, 2014.

  22. Jiang N., Zhang J. X., Li H. T., and Lin X. G., Semi-automatic building extraction from high resolution imagery based on segmentation, IEEE 2008 International Workshop on Earth Observation and Remote Sensing Applications, China, pp 1–5, 2008.

  23. Kim T., Lee T., and Kim K., Semiautomatic building line extraction from IKONOS Images through monoscopic line analysis, Photogrammetric Engineering and Remote Sensing, United States of America, vol. 72/issue 5, pp 541–549, 2006.

  24. Yeom J., and Kim Y., A regular grid -based Hough transform for the extraction of urban features using high -resolution satellite images , Remote Sensing Letters , United Kingdom, vol. 6/issue 5, pp 409–417, 2015.

  25. Vapnik V., Statistical learning theory, United States of America, 1998.

  26. Laben C. A., and Brower B. V., Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening, US Patent, United States of America, 2000. 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org

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