在分析比较现有角点提取算法的基础上，将SUSAN算法用于提取高分辨率影像的角点及影像匹配。针对试验中原算法在不规则纹理区提取大量冗余角点及对强边缘敏感等问题，提出按照影像局部和整体对比度的关系自适应计算灰度差阈值，使用矩形模板从边界上确定USAN区域(核值相似区)可能的范围，再检测角点的改进思路。试验证明改进后算法提取的角点位置更为准确，有效剔除了原算法检测结果中的冗余角点，提高了影像匹配速度。

On the basis of analyzing and comparing existing corner detection algorithms, SUSAN algorithm has been adopted and improved in this paper for corner detection and image marching for high-resolution images. Aiming at some problems existed in the traditional SUSAN algorithm such as over detection and edge sensitive for irregular texture image area, we proposed an improved algorithm. Firstly, the threshold of gray difference is calculated adaptively according to the relationship between local and global image contrast. Secondly, rectangular template is adapted to determine the possible limits of USAN region from the edge. Finally, the corners are detected based on above two steps. Experiments show that the corners location is detected more accurately with the improved algorithm, and the results are more reliable and less redundant with much higher speed in image marching.