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SIR-C polarimetric image segmentation by neural network

Conference Paper
Publication Date:
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).
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Algorithms; Image segmentation; Image understanding; Moisture; Neural networks; Radar measurement; Sensors; Soils; Surface roughness; Synthetic aperture radar; Grey level statistics; Image interpretation; Polarimetric image segmentation; Salina area; Self organizing map network; Urban area; Radar imaging
List of contributors:
Satalino, Giuseppe; Pasquariello, Guido
Authors of the University:
SATALINO GIUSEPPE
Handle:
https://iris.cnr.it/handle/20.500.14243/217848
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http://www.scopus.com/inward/record.url?eid=2-s2.0-0029702527&partnerID=40&md5=6f5bfbde0e714845c42ec33c8160c4bf
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