To address the time-consuming problem of image registration in the scale-invariant feature transform(SIFT) algorithm, a curvature scale space (CSS)-SIFT composite image registration algorithm is proposed in this paper. First, the CSS-SIFT algorithm uses the CSS algorithm to extract image features. Image feature descriptors are then generated and reduced by the optimized SIFT algorithm. Finally, an optimized two-way matching algorithm based on Euclidean and Manhattan distances is used for matching.A simulation experiment is conducted using simulation software, and six parameters of index data are employed, including the number of image features, number of matches, number of correct matches, registration accuracy, registration time, and registration time decline rate. Statistical results show that the CSS-SIFT algorithm performs as well as the following algorithms in terms of accuracy of image registration: traditional SIFT, traditional speeded-up robust features, Forstern-SIFT, Harris-SIFT, and Trajkovic-SIFT. In addition, time-consumption of image registration is reduced by 58.45%, 10.68%, 14.84%, 16.21%, and 4.63%, respectively, thus providing an effective solution for image registration.