Danielle Ducrot

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This paper deals with the application of Independent Component Analysis (ICA) as a solution to Blind Source Separation (BSS), in order to pre-process remote sensing multispectral images before we classify them. We analyze the structure of the considered data, and especially show that each recorded image corresponding to a spectral band may be seen as an(More)
The classification of remotely sensed images knows a large progress taking in consideration the availability of images with different resolutions as well as the abundance of classification's algorithms. A number of works have shown promising results by the fusion of spatial and spectral information using Support vector machines (SVM). For this purpose, we(More)
In this paper we present a Markovian method of classification of the satellite images, this method is based on a minimization of the posterior energy by the ICM method (iterated conditionnal mode) with the introduction of constraints of the spatial context. The originality of our method is the variability over the iterations of a temperature factor like in(More)
Edge detection and segmentation are fundamental issues in image analysis. Due to the presence of speckle, which is generally modeled as a strong, multiplicative noise, edge detection in synthetic aperture radar (SAR) images is extremely diicult, and edge detectors developed for optical images are ineecient. Several robust operators have been developed(More)
—The classification of remotely sensed images knows a large progress taking in consideration the availability of images with different resolutions as well as the abundance of classification's algorithms. A number of works have shown promising results by the fusion of spatial and spectral information using Support vector machines (SVM) which are a group of(More)
—The classification of remote sensing images has done great forward taking into account the image's availability with different resolutions, as well as an abundance of very efficient classification algorithms. A number of works have shown promising results by the fusion of spatial and spectral information using Support Vector Machines (SVM) which are a(More)