Point cloud enhancement method based on subsection resampling and surface triangularization

Abstract

The invention discloses a point cloud enhancement method based on subsection resampling and surface triangularization. The method comprises the specific steps that an input point cloud (imag file=' 2013107425845100004dest-path-image001. TIF' wi='13' he='32' / ) is divided to obtain the set (img file='752571des t-path-image002. TIF' wi='37' he='24' / ) of the subsets of the point cloud (img file='835430dest-path-image001. TIF' wi='13' he='32' / ), each subset (img file='2012107425845100004dest-path-imag003. TIF' wi='20' he='32' / ) is resampled, data noise is filtered out, and new point sets (img file='dest-path-image005. TIF' wi='23' he='32' / ) which are more even in space distribution are obtained; the sets (img file='250417dest-path-image006. TIF' wi='40 he='32 / ) of all the resampled new point sets are combined, a new point cloud (img file='dest-path-mage007. TIF' wi='16' he='32' / ) is obtained, the surface triangularization is carried out on the new point cloud (img file='114468dest-path-mage007. TIF' wi='16' he='32' / ), and a triangular mesh model ((img file='397682dest-path-image008. TIF' wi='15' he='32' / ) is obtained. According to the method, an environmental structure is restored accurately, and meanwhile the original edges and corners of the environment are prevented from being smoothed by mistake; different sampling densities are selected according to different model surface shape change intensity degrees, and model representation is more efficient. The point sets are projected to a two-dimensional plane to be triangulated at the part of the model, and the calculation efficiency ratio is higher than that of triangularization directly carried out in a three-dimensional space.

Description

technical field [0001] The invention relates to the field of environmental information collection and point cloud processing, in particular to a point cloud enhancement method based on subsection resampling and surface triangulation. Background technique [0002] Traditional point cloud enhancement methods directly resample the point cloud and then triangulate the surface, or directly triangulate the surface without resampling. For the real environment data collected by the sensor, the noise is relatively large. If the surface is triangulated directly, the triangular mesh surface will be uneven and the model effect will be poor. Even if resampling is performed, although it can increase the point cloud density and achieve a better model approximation effect, it will also weaken the original structure of the environment such as edges and corners due to the smoothing effect of resampling. Contents of the invention [0003] The purpose of the present invention is to overcome ...

AI Technical Summary

Problems solved by technology

For the real environment data collected by the sensor, the noise is relatively large. If the surface is triangulated directly, the surface of the triangular mesh will be uneven and the model effect will be poor.

Even if resampling is performed, although it can increase the point cloud density and achieve a better model approximation effect, it will also weaken the original structure of the environment such as edges and corners due to the smoothing effect of resampling

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