With the development of computer graphics technology, machine vision and virtual reality technology in recent years, 3D reconstruction method through the sequence of images of outdoor scenes has become a key research direction in computer vision and graphics. During the acquisition process of image, due to the measurement equipment and environment, single shot sequence of photos may not be able to extract enough surface information and lead to unable to complete the reconstruction of 3D objects. To solve this problem, fusion method of point clouds from multi-group images is adopted in the thesis. Firstly the color histogram matching is used to complete the supplement image sequence. Next the point cloud from the supplement image sequence is solely calculated. Then the transform parameters in overlap area of different point clouds are computed by using the improved iterative closest point algorithm. Finally the registration and fusion among the point cloud data of different photos is conducted. The experiments show that this method can effectively supplement point cloud data for reconstruction.