Hela Elmannai

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—The presented work deals with the problem of remote sensing data separation and fusion. Multispectral images are acquired from different bands. The collected radiances are the results of many reflections due to the land heterogeneity and the atmosphere. The mixture phenomenon is therefore nonlinear. This work aims to find an adequate nonlinear separation(More)
In this paper, we aim to classify remotely sensed images for land characterisation. The major goal is approaching the natural nonlinear mixture for band observation and then dimension reduction by supervised classification. After that, an unsupervised method combining feature extraction and SVM in investigating to discriminate the land cover for SPOT 4(More)
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