Unsupervised segmentation of SAR image based on multiscale stochastic model
基于多尺度随机模型的SAR图像无监督分割

The presence of speckle in Synthetic Aperture Radar(SAR) images makes the segmentation of such images difficult,either by gray levels or by texture.According to the mechanism of SAR imaging,two unsupervised segmentation methods were proposed based on two class of multiscale stochastic model,namely multiscale autoregressive(MAR) model and multiscale autoregressive moving average(MARMA) model.These models capture the statistical information in a multiscale sequence of SAR image,which is then used to implement unsupervised segmentation of SAR image via multiresolution mixture algorithm.Experimental results over SAR images confirm the proposed segmentation methods are valid.