In order to obtain a complete and high-resolution image of wind turbine blade cracks, image stitching technology is used to stitch multiple high-resolution images into a complete image. Aiming at the problems of difficulty in features detection, low matching rate, and poor stitching quality in wind turbine blade crack images, an image stitching method based on AKAZE algorithm and PROSAC algorithm is proposed. The AKAZE algorithm is used to detect image feature points and generate binary feature point descriptors. Use Hamming distance as a similarity measure to perform brute force matching on feature points. The PROSAC algorithm is used to optimize the feature matching results and calculate the image transformation matrix. The fade-in and fade-out fusion algorithm is used to eliminate splicing traces and obtain a complete blade crack image. The test results show that the method in this paper can detect a rich number of feature points, the matching correct rate is above 95%, the splicing accuracy is about 0.7 pixels, and the splicing speed is improved by 17% compared with the SIFT method. The AKAZE+PROSAC method can better meet the needs of high-resolution wind turbine blade crack images stitching.