Studies On Denoising And Smoothing Of Point-based Mode

Software for processing 3d data, people may obtain raw data representations of real objects with complex shape via a variety of ways, then analyze and process them. This kind method of acquiring and processing data is called reverse engineering, and the obtained data are mainly classied into CT data, MRI data, and irregular 3D point-based data.Due to a variety of physical factors of the acquisition procedure, the derived raw models always are prone to various kinds of undesirable noise and distortions. The purpose of 3D denoising is to remove the effects caused by isolated noises from the derived surface whilst preserving the appearance of geometrically sharp features and minimizing distortion locally or globally.In this paper, we focus on the research on denoising and smoothing of 3D geometry and propose a number of novel algorithms on smoothing/denoising for point-based models, and main contributions include:· A introduction to classical 3D smoothing algorithms as well as some new smoothing/denoising methods in the recent years is presented. After analyzing and summarizing the fundamental theories, the disadvantages and advantages of different methods are induced. And brief comparisons between various algorithms on their theoretical basis, applied environments and numerical implementations are presented.· As for the existing models, to artificially append the noise, a noise model based gauss algorithm was proposed, many practically noise model under different conditions can be generated using the algorithm, the requirement of the experiment can be satisfied, the reliability and robustness of the trim algorithm can be validated, and support corresponding conditions for the research.· On the point-based model noise intensity algorithm for 3D Meanshifit process, a noise intensity algorithm based on the enhanced keeping characters and volume of the noise was proposed. A global k domain based noise was used to restrict and adjust the filter direction, to make the budge direction of Meanshift be close to the normal of point, force the excess volume shrink, which makes the point uniformly diffused to the clusting domain, effectively prevent the problem of vertex shift.