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.