In this paper, the results of the segmentation process of polarimetric multiband SAR images are shown. Purpose of the work is the image interpretation in absence of ground-truth. The segmentation process is performed by the Self Organizing Map network which is an unsupervised neural network. The objective of the segmentation is the selection of homogeneous regions on the image and the results are evaluated in terms of grey level statistics on same restricted areas (urban and salina areas).
SIR-C polarimetric image segmentation by neural network
Satalino G;Pasquariello;
1996
Abstract
In this paper, the results of the segmentation process of polarimetric multiband SAR images are shown. Purpose of the work is the image interpretation in absence of ground-truth. The segmentation process is performed by the Self Organizing Map network which is an unsupervised neural network. The objective of the segmentation is the selection of homogeneous regions on the image and the results are evaluated in terms of grey level statistics on same restricted areas (urban and salina areas).File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


