With the rapid development of aviation unmanned system technology, distributed airborne image stitching technology has become a high-profile research field. In this paper, an improved algorithm based on the APAP image stitching algorithm is proposed to solve the problems of large parallax and complex spatial geometric transformation in distributed airborne image stitching. The algorithm employs deformation processing, linear homography smooth extrapolation to global transformation, and mesh division method, which effectively eliminates blurred ghosting, reduces projection distortion at edges, and improves the operating efficiency of the algorithm. In experiments under multiple scenarios, the proposed algorithm exhibits smaller alignment errors and higher image quality metrics, including root mean square error, peak signal-to-noise ratio, structural similarity, and image entropy, among others. Moreover, when performing large-scale image stitching, the improved algorithm can achieve large-scale stitching of 154 images to obtain a 10 k×10 k high-resolution panoramic image, with a stitching time of 138 s. Therefore, the improved algorithm has important practical application value and can be used in the practical application of distributed airborne image stitching.