Title :
Unsupervised classification of polarimetric SAR images using neural nets
Author :
Belhadj, Ziad ; Yahia, Mohamed
Author_Institution :
SUPCOM, Tunisia
Abstract :
Classification of earth terrain components using fully polarimetric SAR images is one of many important application of radar polarimetry. In this paper, we are interested in unsupervised classification method because of their rapidity, automatic criterion and their independency on the images to be classified.
Keywords :
image classification; neural nets; radar imaging; radar polarimetry; remote sensing by radar; synthetic aperture radar; terrain mapping; unsupervised learning; earth terrain component; fully polarimetric SAR images; neural nets; radar polarimetry; synthetic aperture radar; unsupervised classification method; Backpropagation algorithms; Clustering algorithms; Earth; Implants; Neural networks; Radar imaging; Radar measurements; Radar polarimetry; Synthetic aperture radar; Topology;
Conference_Titel :
Information and Communication Technologies: From Theory to Applications, 2004. Proceedings. 2004 International Conference on
Print_ISBN :
0-7803-8482-2
DOI :
10.1109/ICTTA.2004.1307764
