The synthetic aperture radar (SAR) image terrain classification algorithm combining the respective characteristics of Beta-prime (BP) statistic model and quadratic Gamma discrimination (QGD) classifier is presented.Through classifying background clutter and target by BP model
and classifying natural target and man-made target by QGD classifier
this algorithm can cluster the SAR image into shadow
background clutter
natural target and man-made target.It can offer not only the information of background clutter and natural target
but also the potential target chips for target recognition process.