ing at the applications of moiré fringes in fine measurement, a super-resolution algorithm is proposed based on local self-similarity and deblocking post-processing. In this algorithm, with the local self-similarity of moiré fringes, the initial high-resolution images are first obtained through an interpolation of the original low-resolution images. Then the optimal matching low-resolution block corresponding to each high-resolution image block is searched. The prior knowledge is extracted from the high- and low-resolution image blocks and thus the super-resolution reconstruction of a single-frame image is realized. In addition, the blocking artifacts are introduced in the reconstructed results after the blocking operations. As for this problem, a post-processing algorithm for quickly eliminating blocking artifacts is simultaneously proposed. The results show that the combination of the proposed two algorithms can effectively improve the image quality and simultaneously eliminate the blocking artifacts in the reconstruction process of images. The algorithm does not relay on external images and has a low computational complexity, suitable for the super-resolution reconstruction of moiré fringe images.