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SAR Images Classification Using Fuzzy Subsethood Operator

Chapter
Publication Date:
2002
Short description:
SAR Images Classification Using Fuzzy Subsethood Operator / Angiulli, Giovanni; Barrile, Vincenzo; Versaci, Mario. - 82:(2002), pp. 1466-1470. (Intervento presentato al convegno KES02 - IKOMAT02 tenutosi a Podere d'Ombriano, Cremona (Italy)).
abstract:
The availability of synthetic aperture radar (SAR) images makes practical many geophysical applications. One of them is the classification of terrain structures. In the past years a number of techniques have been developed to classify ground terrain types from SAR images. The conventional approach to classification which assigns a specific class for each region in an image is often inadequate because the area covered by each region may embrace more than a single class. Fuzzy set theory, which has been developed to deal with imprecise information, can provide a more appropriate solution to this problem. In this work has been developed a new supervised fuzzy classification method based on the use of Subsethood Operator. Results of classifying a SAR image are presented and their accuracy is analysed and compared with other standard classification techniques.
Iris type:
2.1 Contributo in volume (Capitolo o Saggio)
Keywords:
Image Classification; Fuzzy Subsethood Operator; Neuro Fuzzy Networks
List of contributors:
Angiulli, Giovanni; Barrile, Vincenzo; Versaci, Mario
Authors of the University:
ANGIULLI Giovanni
BARRILE Vincenzo
VERSACI Mario
Handle:
https://iris.unirc.it/handle/20.500.12318/10042
Book title:
Knowledge-based intelligent information engineering systems and allied Technologies
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