SAR image automatic target recognition based on local multi-resolution features

Synthetic aperture radar (SAR) image automatic target recognition is an important direction in image recognition domain. Inspired by the vision cell receptive field model, an image processing method was developed based on multi-resolution decomposition which starts from a local point in the image. The method uses a simple 8-neighborhood orthonormal basis for image multi-level filtering and sampling to obtain the difference of Gaussian liking scale space of the original image. The method was then applied to the feature extraction of the SAR image targets in the MSTAR dataset. Based on the integration of multi-level features, a multi-scale kernel method is utilized in the SVM model. The features from different levels of decomposition images are mapped into the feature spaces by kernel functions with different scales respectively, with the multiple kernel matrixes then integrated. Tests on the MSTAR dataset show that the method has a high correctness rate and classifies targets simply and rapidly. The method can also be conveniently used for the segmentation and automatic target recognition of multi-class/multi-target in SAR image scenes, with relatively strong robustness against the speckles.