Because of the stronger noise

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.