PolSAR images classification through GA-based selective ensemble learning

With multiple channels, Polarimetric SAR (PolSAR) contains abundant target information and anti-jamming ability, which can improve the ability of target discrimination and image interpretation. The classification problem of PolSAR has become one of the most urgent problems to be solved in PolSAR application with the improvement of PolSAR technology. Due to the complexity of multiple-dimensional classification, single classifier often considers one issue and ignores other aspects, which result in great deviation from the real situation. Integration of multiple classifiers can overcome the above problem; however it is not mean the more numbers of classifiers, the better the result. Therefore, this paper introduces a PolSAR image classification method of selective ensemble learning based on genetic algorithm, which can select several classifiers with better performance from the multiple classifiers to get the excellent result.