Polarimetric SAR image classification with the maximum curvature of the trajectory in the eigen space converted from the polarization signature Original Research Article

A method for polarimetric SAR image classification based on maximum likelihood classification with the maximum curvature of the trajectory of in the eigen space converted from the polarization signature is proposed. One of the examples of the sea ice classification is shown. The classification performance of the proposed method is compared to the existing methods based on the maximum likelihood classification with (1) fully polarimetric SAR data (received power), (2) the received + H + A + (α), (3) the received power + odd + even + diffuse of the scattering components. The RI-SAR data of the sea of Okhotsk and Tsukuba in Japan which are acquired on 23 February 1999 and on September 30 1997 are used. It is found that the proposed method is superior to the existing methods in terms of the classification performance at the 95% of confidence interval as well as the kappa coefficient.