Classification of very high resolution SAR image based on convolutional neural network

Abstract

The new advanced very high resolution (VHR) synthetic aperture radar (SAR) sensor is a kind of high-tech imaging radar developed rapidly in recent years, and it can get even less than 1 m high resolution SAR image. The feature of the VHR SAR image is different from the low or medium resolution SAR image and it contains more abundant information, so the traditional SAR image classification methods can't be directly applied in VHR SAR image classification. In order to achieve high precision classification performance of the VHR SAR image, convolutional neural network (CNN), a kind of representative deep learning method, is applied in this paper. Compared with the traditional supervised classification methods, such as minimum distance and maximum likelihood, the CNN method obtained better classification result with 97.0% average accuracy. The experiments demonstrate that the CNN is an effective and favorable classification method for VHR SAR image classification.