Wishart RBM based DBN for polarimetric synthetic radar data classification

Deep Belief Network (DBN) is a classic deep learning model, and it can learn higher feature and do better classification job. We combine DBN´s basic component Restricted Boltzmann Machines (RBM) with the statistic distribution of Polarimetric SAR (PolSAR) data. Based on it, we develop a deep learning classification method that is suitable for PolSAR data. To verify the effectiveness of the method, a real PolSAR dataset is tested. Experiment result confirms that the proposed method provides fine improvements both in classification accuracy and visual effect.