SAR image spherical local embedding modeling and classification method

Modeling for SAR target is one of key technologies for SAR image interpretation and application. Recently, modeling based on manifold learning develops so that it is applicable to model for SAR image which is based on the imaging mechanism of microwave scattering. In this paper, SLE method was used to model for SAR image. In essential, this method did nonlinear dimensionality reduction on high dimensional SAR image data, capturing the corresponding low-dimensional manifold structure indicating intrinsic features. It could be used to represent and interpret objects more precisely, due to weakening the redundant information of original high-dimensional data. Additionally, the reduction of dimensionality greatly reduced the computational complexity. To verify its effectiveness, this paper applied it on SAR image scene classification, using KNN classifier and SVM classifier. The experiment results demonstrated that our method was effective and had a good prospect.