In order to reduce the high computing complexity of Affine Scale Invariant Feature Transform (ASIFT) algorithm, a robust and rapid matching method for large angle aviation oblique images based on homography transformation was proposed, which was named H-SIFT. Firstly, the homography matrix between the two oblique images was calculated by making full use of the rough Exterior Orientation (EO) elements of the images, then a homography transformation was made to the left image to get its rectified image for eliminating geometric distortion, scale and rotation. Secondly, the matches between the rectified image and the right image were got by using Scale Invariant Feature Transform (SIFT) algorithm. During the matching process, the coarse matches were got by using two matching constraints, Nearest Neighbor Distance Ratio (NNDR) and consistency checking, then the false matches in them were eliminated by using the RANdom SAmple Consensus (RANSAC) algorithm. Finally, as the matching points on the rectified image were got, the corresponding matching points on the left image were calculated by using the homography matrix. The experiments on three pairs of typical oblique images obtained by Si Wei Digital Camera 5 (SWDC-5) demonstrate that the matching points obtained by the proposed algorithm are significantly improved in the computation efficiency, quantity and distribution than ASIFT algorithm, as the proposed algorithm not only takes just about 0.93%, 0.88%, 0.97% time of ASIFT algorithm, but also gets the correct matching points about 2.18, 1.31, 1.70 times of ASIFT algorithm.