The invention provides a multi-vision image dense
coupling fusion method and
system based on multiple characteristics and multiple constraints. The method comprises the following steps: according to the multiple constraints, respectively selecting a plurality of images to be coupled for each
reference image, obtaining to-be-coupled image sets, and the reference images and corresponding
coupling image sets form
coupling models; for each coupling model, by use of multi-vision constraint conditions, carrying out half global dense coupling to directly generate a dense coupling result of a single coupling model, and obtaining a corresponding elevation graph; according to elevation smooth constraints between grid points, under the condition of a minimum
global energy function, carrying out fusion on the dense coupling results of the multiple coupling models; and through combination with surface characteristics and line characteristics, carrying out
point cloud optimization to generate final point clouds. According to the technical scheme provided by the invention, a reasonable
stereo image pair can be automatically selected, coupling results are enabled to be more accurate and reliable by use of multi-vision information, optimal multi-vision fusion results with global significance can be obtained, and the point clouds generated through the optimization are finer.