Aiming at the problem of poor performance of the scale-invariant feature transform algorithm when registering optical and synthetic aperture radar images, this paper proposes an improved optical and SAR scale-invariant feature transform based on registration algorithm for optical and SAR images. First, the nonlinear diffusion filter is used to create the nonlinear diffusion scale space of optical and SAR images, and the multiscale Sobel operator and the ratio of exponentially weighted averages operator are used to compute the consistent gradient information of optical and SAR images, respectively. Then, the image block strategy is adopted, the scale space is divided into blocks after skipping the first layer of the scale space, and Harris feature points are extracted based on consistent gradient information to obtain stable and uniform point features. To overcome the nonlinear radiation difference between the images, the gradient location and orientation histogram descriptor template are used to build the descriptor. Finally, for feature matching, the Euclidean distance is used and the fast sample consensus algorithm is used to eliminate mismatches. The experimental results show that compared with the scale-invariant feature transformation algorithm combining position, scale, and direction and the OS-SIFT algorithms, the algorithm's matching rate is considerably improved, and the root mean square error is relatively low.