In processing high-resolution remote sensing images, the SIFT algorithm has large calculation burden and great amount of time cost.To solve the problems, we made improvement to the SIFT algorithm on extreme point detecting and similarity measurement.Firstly, the improved algorithm uses the 14 points that are closer to the detecting point and have higher weight instead of the 26 points of the SIFT algorithm to detect the extreme points, which can reduce calculation amount for extreme point detection.Secondly, in the similarity measurement of SIFT feature vector matching, the linear combination of Manhattan distance with Chebyshev distance is used instead of Euclidean distance, which is more simple and can decrease the computation complexity and improve the efficiency of matching.Finally, simulation results prove the effectiveness of the algorithm by using the measured remote sensing data.