Aiming at the problems of ghosting, distortion and unnaturalness in processing complex images with large parallax using the common aerial image mosaic algorithm, this paper proposes an aerial image mosaic algorithm based on linear feature constraint mesh deformation. The algorithm adds global similarity and linear structure protection constraints on the basis of the APAP(as-projective-as-possible) algorithm. Firstly, the features of points and lines are detected to estimate the homography distortion in the overlap region of the image. Then, the image is divided into several local image blocks to establish grid optimization models. According to the grid vertex coordinate set, a total energy function containing different features of image distortion is defined. On the premise that the local homography ensures the alignment of the overlap region provided by the APAP algorithm, the global similarity constraint of the NISwGSP algorithm as well as the linear structure constraint are used to improve the naturalness of stitching for the non-overlapping region. Finally, the optimal grid vertex set can be solved to guide the grid deformation and complete the aerial image mosaic in the sparse linear system. The experimental results show that the proposed algorithm can reduce the problems of ghosting and non-overlapping area distortion. Compared with AutoStitch, APAP, AANAP, SPHP and other advanced methods, the proposed algorithm is more natural in stitching effect and is more suitable for the aerial image mosaic task with a certain angle of view.