the stable performance of optical method degrades obviously in SAR image scale invariant feature extraction. To deal with it
we propose a new SAR image scale invariant feature extraction algorithm based on Harris operator. As well known
Harris operator has well stable performance in single scale image feature point detection. In this paper
we first adapt it to multi-scale image and select the features positions by analyzing the stability of Harris measure local maximum points. Then to improve the speed
the recursive Gaussian filter is designed to replace the convolution filter. At last
the feature descriptor is designed based on the gradient information of feature point neighborhood. Based on real SAR images
the experimental results show that an obviously stable performance improvement can be obtained through our algorithm.