A new method for fast image registration based on improved Harris-Sift algorithm is proposed. Firstly, classic Harris algorithm is improved by building Gaussian scale space to extract scale invariant Harris corners and they are refined to sub-pixel corners using Forsnter algorithm. Then the SIFT descriptor is utilized to characterize those feature points and the matching procedure is carried out via randomized kd trees. At last, RANSAC is used to remove wrong matches and the optimal transform parameters are estimated using the least square method to accomplish the image registration process. The experimental results demonstrate that compared with the classic SIFT algorithm the proposed method decreases the cost time of the registration procedure mostly by 64% while almost keeping the same performance.