17 December 1996 Multisource classification of SAR images with the use of segmentation, polarimetry, texture, and multitemporal data
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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.
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Franck Sery, Danielle Ducrot-Gambart, Armand Lopes, Roger Fjortoft, Eliane Cubero-Castan, 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); doi: 10.1117/12.262886; https://doi.org/10.1117/12.262886
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KEYWORDS
Polarimetry

Image segmentation

Curium

Synthetic aperture radar

Speckle

Image classification

Reflectivity

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