Automatic Target Classification in SAR Images by Multilayer Back Propagation Neural Network

In this study, a novel descriptive feature extraction method of Discrete Fourier transform and neural network classifier for classification of Synthetic Aperture Radar (SAR) images is proposed. The classification process has the following stages (1) Image Segmentation using statistical Region Merging (SRM) (2) Polar transform and Feature extraction using Discrete Fourier Transform (3) Neural Network classification using back propagation. The algorithm has been applied for the three classes of military manmade objects (metal objects) in SAR imagery is using MSTAR public release database. Experimental results are presente.