Multiscale probabilistic neural network method for SAR image segmentation

This paper proposes an effective multiscale method for the segmentation of the synthetic aperture radar (SAR) images via probabilistic neural network. By combining the probabilistic neural network (PNN) with the multiscale autoregressive (MAR) model, a classifier, which inherits the excellent strongpoint from both of them, is designed. The MAR models are utilized to extract the multiscale feature of SAR image, which is the input of the network. The PNN is trained by the proposed algorithm, and then the SAR images are segmented by the trained network. The experimental result demonstrates the effectiveness and efficiency of the proposed method.