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Supervised classification for synthetic aperture radar image

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3 Author(s)
Dupuis, X. ; Univ. de Nice-Sophia Antipolis, Valbonne, France ; Mathieu, P. ; Barlaud, M.

This paper deals with the supervised classification of synthetic aperture radar (SAR) images. Our approach is based on two criteria, which explicitly take into account the intensity of the SAR image and the neighborhood classes, similarly to the Pots model, but weighted by a discontinuity map. The high level of noise involves numerous classification errors. We classify a restored image filtered with a well-adapted algorithm to clustering. Moreover, we isolate the texture of SAR images in order to help the classification. Finally, we present results on real SAR images

Published in:

Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on  (Volume:6 )

Date of Conference:

15-19 Mar 1999

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