Learning based decomposition for polarmetric SAR images

In this paper, the algorithm of K-SVD learning dictionary is applied to target decomposition for polarimetric SAR (PolSAR) images. This algorithm can obtain a set of bases self-adaptively according to the data on each channel of PolSAR, to make polarimetric data become more differentiated on this set of bases. Experiments on the data acquired through polarization SAR equipment developed by China for the first time show that features decomposed through K-SVD algorithm perform better than features based on the physical mechanism of PolSAR when used for classification.