Sea-Land Segmentation of Polarimetric SAR Images Based on Thresholding USING Polarimetric Likelihood Ratio

A sea-land segmentation method in polarimetric SAR images is proposed based on thresholding using polarimetric likelihood ratio in this article. Firstly, the volume scattering power is extracted based on three-component decomposition. Then, a typical sampling region of the sea is extracted based on the mean and variance of the region to determine the range interval of the threshold. Finally, the optimal threshold such that the polarimetric likelihood ratio between the sea and land region reaches the maximum is searched in the interval. Experiments of different sensors of data in San Francisco including AirSAR, RADARSAT-2, TerraSAR-X and Gaofen-3 show that both the precision and recall rates of the proposed method are higher than 90%, significantly surpassing those of the comparison methods.