Two or more image stitching problems with more texture and higher noise were studied. When two images are spliced, the extraction of image feature points has a great influence on the image splicing results. The classical SIFT algorithm is a better local feature point extraction algorithm. For images with more texture and higher noise, the SIFT algorithm extracts a large number of feature points, which affects the accuracy and speed of matching. In this study, based on structural information-based image matching algorithm called SKM, the RTV algorithm is used to extract the information structure of the image, and the texture noise in the image is effectively removed. After denoising, the SIFT algorithm is used to extract feature points for matching. Finally, RANSAC algorithm is used to screen matching points to improve the accuracy. The transformation matrix H obtained by SKM algorithm acts on the original image to complete image mosaic.