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In this paper the problem of the supervised classification of satellite images is considered. A new image classification method focused on application under conditions when the training sample is (in particular, considerably) contaminated is proposed. The method is based on using the Dempster–Shafer evidence theory and is applicable both for hyperspectral and multispectral satellite images. Problems of organizing the supervised classification process and content of its constitutive procedures are presented. The developed method has been implemented algorithmically and in software. Results obtained in the classification of hyperspectral images by the proposed method testify to its efficiency.

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