02 Sep 2012 to 02 Sep 2012
Many methods to interpret polarimetric SAR images were directed towards the identification of polarimetric response of natural and artificial targets. Many procedures also have been developed to interpret and identify the scattering mechanism in a resolution cell or in a target , . In the two last decades, a great progress was made in scattering process decomposition and target type discrimination, including the decomposition of the response of the target and the description of the dominant mechanisms of diffusion for various objects. Scattering mechanisms are described, for natural targets, by the eigenvalues and their associated eigenvectors of covariance or coherence matrix. The satellite polarimetric data does contain more information than the corresponding single polarization data. SAR polarimetry allows a discrimination of different types of scattering mechanisms because polarimetric signatures depend on the scattering process. The polarimetric classification is one of the most important applications of radar polarimetry in remote sensing. We present in this paper an unsupervised classification method that identifies target scattering characteristics. We used the entropy /alpha classification based on the Cloude/Pottier decomposition. Results are obtained using coherency matrix. We had a fully polarimetric image that is acquired from Quebec in Canada in the C band provided by the Canadian Centre for Remote Sensing CCRS.