The invention relates to an image splicing method based on improved image fusion. The method mainly settles technical problems of low real-time performance, splicing seam and ghost in prior art. The method comprises the steps of respectively performing characteristic point extraction on a target image and a reference image by means of an A-KAZE algorithm, and establishing a characteristic description subset; constructing a KD-tree, establishing a characteristic point data index, matching the characteristic point by means of a bidirectional KNN matching algorithm, obtaining an initial matching result, performing external point elimination and internal point reserving on the initial matching result through a RANSAC algorithm, and finishing image registering; and performing image fusion by means of an improved Laplace multi-resolution fusion algorithm based on a splicing seam, wherein the step comprises an optimal splicing seam by means of dynamic planning method, limiting a fusion range according to the optimal splicing seam, and finally performing fusion by means the Laplace multi-resolution fusion algorithm in a fusion range, thereby finishing image splicing. The image splicing method settles the problems in a relatively good manner and can be used in image splicing.