Method of multi-source image point cloud fusion modeling
Aiming at the problem of low degree of refinement and blurred texture when modeling large scenes from a single data source,this paper proposed a method of multi-source image point cloud fusion modeling. Firstly,the oblique image and the ground close-range image data were respectively adjusted by the beam method,and the collinear condition equation was employed as the mathematical model to obtain the oblique image point cloud and the ground close-range image point cloud. The coordinate of the two point cloud data was unified to realize the point cloud fusion. Then,the grid model was constructed for the fusion point cloud data,and the laser point cloud was used as the reference point cloud to evaluate the accuracy of the grid model. Finally,seamless texture mapping was performed on the grid model. The experimental results show that the accuracy distance errors of the grid model obtained by this method and the single oblique image are 38.36 mm and 66.12 mm,respectively. The multi-source image point cloud fusion improves the accuracy of the grid model reconstruction, and the three-dimensional model constructed by this method is more complete,more accurate,and clearer than the single data source in the structure,accuracy,and texture.
万方数据
维普
