In-situ inspection and maintenance of wind turbine blades play a crucial role in ensuring the safe operation of wind turbines. Currently, the mainstream UAV inspection method requires panoramic stitching of wind turbine blade images to further locate and analyze minor blade defects and assess the overall blade condition. An improved image stitching technology based on NCC algorithm is proposed to solve the problem of difficult stitching caused by single structure and sparse texture of wind turbine blades. Canny edge detection algorithm is used to extract the blade edge and filter the duplication to get the boundary coordinates, NCC algorithm traverses the blade boundary coordinates for searching and matching to optimize the search strategy and speed up computation while increasing the weight of key information to improve the stitching accuracy, and combining image pyramid coarse-fine matching thoughts to further speed up the algorithm. Finally, the spatial corresponding relation is obtained according to the optimal matching position to achieve stitching. The experimental results show that the matching time of the proposed method is about 6% of the original NCC algorithm and 3%~10% of other classical gray matching algorithms, and lower than other improved NCC algorithms. The stitching success rate is 94.74%, which is higher than all comparison methods, and finally, the visible panoramic image of the wind turbine blade is obtained successfully, demonstrating its good stability in panoramic stitching of large-size wind turbine blades visible images.