Abstract
In the framework of the analysis of remote sensing images, the pixel mixture is a difficult task to solve. As it is considered that a mixture of pure elements is observed, it is necessary to identify them and to determine their proportions. Thus we associate statistical methods of Blind Source Separation (BSS) to complementary techniques of classification. Our purpose is developed and illustrated through an application on images for which a ground analysis was carried out. A comparison between a statistical approach and a clustering one is performed. Even if the BSS approach does not provide the classes associated to the ground analysis, it allows us to refind these classes from a simple learning.
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© 2004 Springer-Verlag Berlin Heidelberg
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Bijaoui, A., Nuzillard, D., Barma, T.D. (2004). BSS, Classification and Pixel Demixing. In: Puntonet, C.G., Prieto, A. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2004. Lecture Notes in Computer Science, vol 3195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30110-3_13
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DOI: https://doi.org/10.1007/978-3-540-30110-3_13
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