Method Study of Point Model Fast High Quality Rendering Based on KD-Tree

In order to achieve fat and high quality rendering for point model, anisotropic quantitative method is proposed. After having used this method, the coordinate figures of sampling points in point model were quantified again; and the quantitative results have been represented as encoding of space partition methods and results in the process of constructing KD-tree. The paper proposed a data compression method in multiresolution structure and realized multiresolution rendering of point model by traversing the KD-tree breadth-first. It established the details control of multiresolution rendering, improved the drawing efficiency of point model. The simulation study was carried out in the paper. Results show that the method could not only reduce the geometry data volume of point models directly, but also reduce the sampling point number without debasing the numerical precision of the model geometry data, so as to further reduce data volume of point model. Some experimental results demonstrate that the algorithm is fast, and can achieve high quality rendering of point model.