Support vector machine segmentation of SAR images based on MARMA model

According to the characteristics of SAR imagery,the support vector machine segmentation of SAR images was proposed based on multiscale autoregressive moving average(MARMA) model,which can capture the statistical scale-dependency of SAR images.Firstly,the multiscale sequences of SAR image were constructed.Secondly,methods for establishing MARMA model and extracting the multiscale stochastic characteristics of different SAR texture images were investigated.Finally,the characteristic vectors were classified using generalized weighted SVM.Experiments show the efficiency of the proposed algorithm.