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

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.