Segmentation of SAR Image Using Mixture Multiscale ARMA Network

Abstract. A mixture multiscale autoregressive moving average (ARMA) network is proposed for unsupervised segmentation of synthetic aperture radar (SAR) image. The network combines the multiscale analysis (MA) method and the feedforward artificial neural network (FANN), thus maintains some of the characteristics of the MA method and the FANN respectively. A corresponding learning algorithm is derived based on the Akaike’s information criterion (AIC) and genetic algorithm (GA). Experimental results on SAR images are shown to validate the presented network and learning algorithm.

• Type: Conference
• Year: 2005
• Where: ICNC
• Authors: Haixia Xu, Tian Zheng, Fan Meng
• Keywords: Artificial Neural Network, ICNC 2005, Learning Algorithm, Synthetic Aperture Radar