Paper Title :Decision Level Fusion Of High Resolution Satellite Data For Urban Area Analysis
Author :Gacem.A, Berrached.N, Merad Boudia.S.
Article Citation :Gacem.A ,Berrached.N ,Merad Boudia.S. ,
(2016 ) " Decision Level Fusion Of High Resolution Satellite Data For Urban Area Analysis " ,
International Journal of Electrical, Electronics and Data Communication (IJEEDC) ,
pp. 21-24,
Volume-4,Issue-4
Abstract : In the field of multi-source data fusion, fusion of multispectral and panchromatic remote sensing data in urban
area has attracted more attention. Multi-source data has been remarkably increased for classification. This is because, the
different sources may provide more information, and fusion of different information can produce a better understanding of
the observed site. This paper addressed the use of a decision fusion methodology for the combination of multispectral and
panchromatic data in urban area. The proposed method applied a support vector machine (svm)-based classifier fusion
system for fusion of the multi-source data in the decision level. First, radiometric feature are extracted on multispectral data.
Then, svm based rbf kernel classifiers are applied on each feature data, and on the panchromatic data. After producing
multiple of classifiers, two comparative data fusion techniques are applied as a classifier fusion method to combine the
results of svm classifiers form the data sets. Experimental results show that the proposed data fusion method improved the
classification accuracy and kappa coefficient in comparison to the single data sets. The results revealed that the overall
accuracies of svm classification on the multi specral and the panchromatic data separately are 60.3% and 59.1%, while our
decision fusion methodology with majority voting technique receive the accuracy up to 88.6%, and dempster shafer receive
the accuracy up to 94.7%.
Type : Research paper
Published : Volume-4,Issue-4
Copyright: © Institute of Research and Journals
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Published on 2016-05-03 |
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