Statistical and bilateral filtering point cloud denoising method based on improved neighborhood search

Abstract

The invention discloses a statistical and bilateral filtering point cloud denoising method based on improved neighborhood search, and the method comprises the following steps: 1, carrying out the processing of point cloud data through employing a statistical filtering algorithm based on improved neighborhood search, and obtaining the processed point cloud data: 1.1, obtaining a point cloud two-dimensional plane projection drawing; 1.2, carrying out grid division to obtain a plurality of rectangles; 1.3, primarily removing outliers; 1.4, calculating an average distance corresponding to any point p; 1.5, calculating an average distance mu and a standard deviation sigma; 1.6, calculating a maximum threshold value dmax, and removing outlier noise points; and 2, performing bilateral filtering on the processed point cloud data obtained in the step 1 to obtain filtered point cloud data. According to the method, the calculation amount is obviously reduced, and the search speed is increased; point cloud data are processed in combination with a bilateral filtering algorithm, large-scale outlier noise points are removed, small-scale noise points in the point cloud are also removed, and the limitation of independent use of the two algorithms is solved.

Description

technical field [0001] The invention belongs to the technical field of 3D point cloud data processing, and in particular relates to a point cloud denoising method based on improved domain search statistics and bilateral filtering. Background technique [0002] With the development of 3D reconstruction technology, 3D point cloud data are more and more widely used in the reconstruction process. Due to its high precision, high resolution and sampling speed, the non-contact point cloud data acquisition method has very important applications in artificial intelligence, industrial production, medicine and other fields. The point cloud data obtained by using 3D laser scanning equipment is in a disordered and scattered state. In addition, due to the influence of factors such as the surface roughness of the target object, equipment accuracy, and environmental lighting, the obtained 3D point cloud is inevitably affected by noise points. The serious impact of noise points will not onl...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a statistical and bilateral filtering point cloud denoising method based on improved neighborhood search, the method projects the point cloud data to a plane and performs grid division, and searches in 9 adjacent rectangles, This solves the problem of slow search speed and large amount of calculation in the traditional statistical filtering algorithm, and the limitation that noise points of different scales cannot be removed well when only statistical filtering or bilateral filtering is used.

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