DocumentCode :
326904
Title :
Spatial and spectral segmentation of satellite remote sensing imagery using processing graphs by mathematical morphology
Author :
Flouzat, Guy ; Amram, Oliver ; Cherchali, Selma
Author_Institution :
Centre d´´Etudes Spatiales da la Biosphere, Toulouse, France
Volume :
4
fYear :
1998
fDate :
6-10 Jul 1998
Firstpage :
1769
Abstract :
The paper presents an autoadaptive method of satellite images segmentation based on a description of the image by graphs. The method presented proposes a new approach using the morphological analysis of the dual graph of the segmentation. A quantification builds an image oversegmented in a connected components set forming a new digital grid. Morphological operations are applied to the graph corresponding to form significant segments by region growing. In the process of growth, the attributes of the regions are kept to enslave the process, but also to contribute to the interpretation of the relations of neighborhood and to understand the physics of detection used
Keywords :
adaptive signal processing; geophysical signal processing; geophysical techniques; graphs; image segmentation; mathematical morphology; remote sensing; adaptive signal processing; autoadaptive method; connected components set; dual graph; geophysical measurement technique; growth; image processing; image segmentation; land surface; mathematical morphology; morphological analysis; new digital grid; oversegmented; processing graph; quantification; satellite remote sensing imagery; spatial segmentation; spectral segmentation; terrain mapping; Biophysics; Image segmentation; Layout; Morphological operations; Morphology; Noise generators; Noise reduction; Physics; Remote sensing; Satellite broadcasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4403-0
Type :
conf
DOI :
10.1109/IGARSS.1998.703646
Filename :
703646
Link To Document :
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