Sea-land segmentation of synthetic ap erture radar (SAR) image is one of the key stages for SAR image applications such as sea target detection and recognition,which are operated only in sea regi ons.A mixture probability models based algorithm is explored to solve the sea-land segmentation problems in complex SAR image.First,Harris corner det ector is employed to detect image patches containing corner points.Furthermore,the image patches are analyzed by mean-sh ift clustering algorithm,and the pixel samples of land regions are obtained.Second,a ccording to pixel samples from land regions,the parameters of probability de nsity function in mixture models are fitted by expectation maximization (EM) algorithm .Finally,land foreground regions are segmented by mixture probability models.Experimental results demonst rate that the proposed algorithm has excellent performance to deal with heterogeneous SAR image.