Polarimetric-spatial classification of PolSAR images based on composite kernel feature fusion

Composite kernel feature fusion is proposed in this paper for solving the classification of polarimetric synthetic aperture radar (PolSAR) images problem. The main idea is that the method of composite kernel encodes diverse information within a new kernel matrix and tunes the contribution of different type of features. The proposed approach is tested on Flevoland PolSAR data set. Experimental results verify the benefits of using both of polarimetric and spatial information by composite kernel feature fusion for the classification of PolSAR images.