To address the problem of fast stitching of tile images with different textures, an image stitching algorithm based on frequency domain is studied. Firstly, the relationship between speed and accuracy in image stitching is analyzed, and the Gaussian pyramid scale space is constructed to reduce the running time of the program. Subsequently, ceramic tile images are registered by phase correlation algorithm. In this process, the subpixel refinement algorithm is combined to compensate for the registration error caused by the decrease in resolution, and a high-frequency feature highlighting strategy based on the Laplacian operator is proposed to enhance the robustness of the phase correlation algorithm. Experiments on tile image stitching with multiple colors and textures show that the proposed algorithm improves the stitching success rate by 60% and 65% in comparison with the algorithms based on SIFT and ORB. Compared with the SURF, H-SURF and FFT algorithms, it improves 9.04%, 7.58% and 4.02% in the SSIM. In terms of running speed, the proposed algorithm is 4 times, 3 times and 2 times higher than SIFT, SURF and H-SURF algorithm, and is only 52% of the traditional Fourier transform-based phase correlation method. The algorithm achieves fast and high-quality image stitching, which meets the imaging requirements of high-resolution tiles in industrial applications.