Point cloud simplification is concerned with reducing the number of redundant points and preserving geometric features, so as to provide a better representation of the underlying surface. In early research, many researchers focused on the moving least squares (MLS) method, volume data, and iterative simplification. MLS is used to construct local surfaces implicitly [3,4], and points are projected to the surface for down sampling. Kobbelt et al [5] simplified point clouds by extracting feature-sensitive surfaces based on volume data. Lipman et al [6] proposed a locally optimal projection (LOP) operator and applied it to raw scanned data with complex shapes. Huang et al [7] developed a weighted locally optimal projection (WLOP) operator based on LOP, which has proven to be less sensitive to noise and has the advantage of producing an evenly distributed point cloud. To reduce the computational complexity of WLOP, Yang et al [8] focused on the decomposition of a point cloud and created multiple output results by Measurement Science and Technology
Optical devices cannot directly obtain the deformation for welding residual stress (WRS) measurement since it is difficult to get the surface characteristic with a high accuracy of measurement. This paper therefore presents a full-field fast method for WRS measurement based on heterodyne multiple frequency phase shift technology. Furthermore, in order to denoise the acquired point cloud, this paper proposes a novel compensation filter method (CFM) to extract accurate surface topography: specifically, to slice the original point cloud into several independent groups, then smooth each group of the point cloud to obtain the compensation value, and finally to fuse the filtered point cloud with the compensation value to extract surface characteristic. As a result, the simulation and the experiment results show that the CFM can reduce the noise by about 80%. It demonstrates that the novel CFM can maintain the features of the point cloud and remove noise efficiently, indicating the high accuracy of the CFM result and the potential to realize fast WRS measurement.
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