Provided is a large-area complex-terrain-region unmanned plane sequence image rapid seamless splicing method which comprises the following steps: to begin with, with air strip arrangement features of unmanned plane image sequence being prior knowledge, carrying out inter-image multiple-overlap SIFT feature point extraction and matching; then, carrying out matching point gross error removing and purifying based on random sample consensus algorithm, and solving transformation parameters of each image in spliced regions in an adjustment manner through an Levenberg-Marquardt algorithm; next, carrying out overlapped region image optimized selection according to the relative position relationship between central projection image point displacement rules and the images, and determining splicing lines; and finally, carrying out image uniform-coloring and fusion at the edge-connection places, and outputting spliced images, thereby realizing mass unmanned plane image seamless splicing. The seamless splicing method helps to improve the extraction efficiency of the SIFT feature points, guarantee the geometric accuracy of the spliced images, and eliminate the tiny color difference at the two sides of the image splicing line, and thus the spliced images with natural color transition and good natural object and landform continuity are obtained.