Aiming at the low time efficiency and poor effect of UAV image stitching, we propose an improved  UAV image stitching algorithm based on AKAZE feature. In image matching phase, the MLDB descriptor is replaced by the BRISK descriptor. The scale information of feature points and root mean square error (RMSE) are taken as the constraint conditions to eliminate false matching points. In addition, the idea of parallel computation is applied to feature point extraction and feature descriptor calculation to improve the time efficiency of the algorithm. In image fusion stage, the RANSAC algorithm combined with the LM algorithm is used to calculate the monotone matrix so as to improve its precision. Finally, the multiband fusion algorithm is used to achieve image stitching. Experimental results show that the proposed algorithm can achieve more accurate and more precise matching results while improving the time efficiency, thus realizing fast and seamless stitching of UAV images.