Unsupervised classification based on H/alpha decomposition and Wishart classifier for compact polarimetric SAR

In this paper, an unsupervised classification for compact polarimetry SAR (C-PolSAR) image is proposed by combining the H/α decomposition with the Wishart classifier. Firstly, H/α decomposition method is applied to the compact polarimetry (CP) data. By analyzing the different (H, a) values corresponding to the three compact polarimetry mode: the π/4, CL, and CC modes, we find that only in the CC mode, different scattering targets are distinguished well by (H, α) values. The decomposition results are used as the initial classification. Then the maximum likelihood classifier based on the complex Wishart distribution is adopted to classify the image iteratively. After four iterations, the classification results are much improved, and the classification details can be identified clearly. We use the AirSAR of San Francisco L-band data to illustrate the effectiveness of the proposed classification method.