Image matching is a fundamental step in remote sensing image processing and analysis. The traditional gray correlation coefficient matching algorithm does not have the rotation invariant feature. SIFT (scale invariant feature transform)algorithm can provide robust matching which is invariant to image scale and rotation. However

for high-resolution remote sensing images with clearer geometric structure and richer texture information

the problem of consuming large memory and slow computing is very prominent. In this paper

the image matching algorithm based on Harris corner and SIFT descriptor is proposed. The experimental results show that

compared to the SIFT algorithm

this algorithm greatly reduces the running time. It preserves the invariance of rotation and change in illumination by using SIFT descriptor

overcomes the shortcomings of the gray correlation coefficient matching algorithm

and has good performance on high-resolution remote sensing image matching.