Morphological operators for segmentation of high contrast textured regions in remotely sensed imagery

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2012
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2012 IEEE International Geoscience and Remote Sensing Symposium. - IEEE, 2012. - S. 3451-3454. - ISBN 978-1-4673-1160-1
Zusammenfassung
We develop a transformation based on morphological filters that measures the contrast of image texture. This transformation is proportional to texture contrast, but insensitive to its specific type. Though the transformation provides a high response in textured areas, it suppresses individual high contrast features that stand apart from textured areas. It can serve as an effective texture descriptor for unsupervised or supervised segmentation of textured regions, provides high accuracy of localization and does not involve heavy computations. The method is robust to variations of illumination and works on different types of images without needing to be tuned. The only parameter is a scale related parameter. We illustrate the use of the proposed method on satellite and aerial images.
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004 Informatik
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Texture detection,texture segmentation,texture contrast descriptor,morphological filters
Konferenz
IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium, 22. Juli 2012 - 27. Juli 2012, Munich, Germany
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Zitieren
ISO 690ZINGMAN, Igor, Dietmar SAUPE, Karsten LAMBERS, 2012. Morphological operators for segmentation of high contrast textured regions in remotely sensed imagery. IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium. Munich, Germany, 22. Juli 2012 - 27. Juli 2012. In: 2012 IEEE International Geoscience and Remote Sensing Symposium. IEEE, pp. 3451-3454. ISBN 978-1-4673-1160-1. Available under: doi: 10.1109/IGARSS.2012.6350678
BibTex
@inproceedings{Zingman2012-07Morph-20883,
  year={2012},
  doi={10.1109/IGARSS.2012.6350678},
  title={Morphological operators for segmentation of high contrast textured regions in remotely sensed imagery},
  isbn={978-1-4673-1160-1},
  publisher={IEEE},
  booktitle={2012 IEEE International Geoscience and Remote Sensing Symposium},
  pages={3451--3454},
  author={Zingman, Igor and Saupe, Dietmar and Lambers, Karsten}
}
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