Multisource classification of SAR images with the use of segmentation, polarimetry, texture, and multitemporal data

Franck Sery; Danielle Ducrot-Gambart; Armand Lopes; Roger Fjortoft; Eliane Cubero-Castan; Philippe Marthon

doi:10.1117/12.262886

17 December 1996 Multisource classification of SAR images with the use of segmentation, polarimetry, texture, and multitemporal data

Franck Sery, Danielle Ducrot-Gambart, Armand Lopes, Roger Fjortoft, Eliane Cubero-Castan, Philippe Marthon

Author Affiliations +

Proceedings Volume 2955, Image and Signal Processing for Remote Sensing III; (1996) https://doi.org/10.1117/12.262886
Event: Satellite Remote Sensing III, 1996, Taormina, Italy

Abstract

The multilook polarimetric maximum likelihood classifier based on the Wishart distribution supposes no variation of the backscattering of the underlying scene. For clutters verifying the 'product model', we here present the use of a K-distribution and compare this classifier to the one based on the Wishart distribution. A simple way to obtain a full polarimetric filter by filtering a set of adequate powers is also given. We show how filtering and segmentation of the raw data improve the classification results.

Citation Download Citation

Franck Sery, Danielle Ducrot-Gambart, Armand Lopes, Roger Fjortoft, Eliane Cubero-Castan, and Philippe Marthon "Multisource classification of SAR images with the use of segmentation, polarimetry, texture, and multitemporal data", Proc. SPIE 2955, Image and Signal Processing for Remote Sensing III, (17 December 1996); https://doi.org/10.1117/12.262886

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