An Unsupervised Classification Method of POLSAR Image

An unsupervised classification algorithm established on the mean-shift over-segmentation is presented in this paper. First,an over-segmentation result is obtained by a mean-shift algorithm and the segmentation patches are treated as "super-pixels". Then,based on Freeman-Durden decomposition,we survey the four different combinations of three basic scattering mechanisms by introducing two new parameters-the scattering power entropy and anisotropy. Finally,the iterative wishart classifier is applied to get the final classification results. The effectiveness of this algorithm is demonstrated by using the German aerospace center's (DLR) E-SAR L-band polarimetric synthetic aperture radar images.