In order to reduce the influence of different scales of noise on the reconstruction of three-dimensional point cloud models, a denoising and simplification algorithm based on the method library of the passthrough filter, statistical filter, radius filter, improved bilateral filter and voxel grid filter is proposed. Firstly, the object is extracted by the passthrough filter. Then according to the distance between the noise points and the model body, the noise points are divided into the small scale noise and the large scale noise. The large scale noise is removed by the statistical filter and the radius filter, and the small scale noise is removed by the improved bilateral filter. Finally, the three-dimensional point cloud is simplified by the voxel grid filter to reduce the space complexity and the accuracy of the proposed algorithm is shown via the triangular mesh reconstruction. The experimental results show that the proposed algorithm can effectively remove different scales of noise existing in the point cloud model and ensure the uniformity of point cloud simplification under the precondition of not destroying the geometrical structure of the point cloud. In addition, this algorithm runs quickly and has high reconstruction efficiency.