Point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction

A combined bilateral filtering and skeleton extraction technology, applied in image enhancement, instrumentation, computing, etc., can solve difficult problems and achieve the effects of easy usability, good robustness, and good denoising effect

Active Publication Date: 2017-05-24
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

Therefore, it is not easy to apply the joint bilateral filtering method to point cloud denoising

Method used

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  • Point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction
  • Point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction
  • Point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction

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Embodiment Construction

[0045] The present invention will be further described below in conjunction with specific examples.

[0046] Such as figure 1 As shown, the point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction provided in this embodiment includes the following steps:

[0047] 1) Use the normal vector difference method to obtain candidate feature points;

[0048] Calculate the normal vector difference between any two points in the neighborhood of each point and sum them up. When the summation value is greater than a certain threshold, mark this point as a candidate feature point, such as Figure 7a shown.

[0049] 2) Extract the skeleton for the candidate point area;

[0050] use l 1 The median skeleton method calculates the candidate feature point area to obtain the skeleton, such as Figure 7b shown.

[0051] 3) Use the skeleton to resample the candidate points to obtain feature points;

[0052] According to the skeleton obtained in ste...

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Abstract

The invention discloses a point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction, which comprises the steps of 1) acquiring candidate feature points by using a normal vector difference method; 2) extracting a skeleton of the candidate points; 3) performing resampling on the candidate points by using the skeleton so as to acquire feature points; 4) endowing each feature point with a multi-normal vector; filtering a point cloud normal vector based on joint bilateral filtering framework; and 6) updating the point position based on the filtered normal vector to acquire a denoised point cloud model. According to the point cloud denoising method, a sharp feature skeleton is firstly extracted to perform analysis on the model structure, so that sharp features of an object are well maintained while denoising is performed, thereby being conducive to dealing with high-intensity noise. The point cloud denoising method has the characteristic of high robustness and has excellent popularization and application prospects.

Description

technical field [0001] The invention relates to the fields of computer graphics and three-dimensional point cloud denoising, in particular to a point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction. Background technique [0002] Most of the 3D model data captured by 3D sensors are saved in point cloud format. Due to the limitation of the accuracy of scanning equipment, such as Microsoft Kinect, the captured point cloud data inevitably contains certain noise. Therefore, point cloud denoising plays a very fundamental and important role in the field of 3D geometry processing. The main challenge of point cloud denoising is how to preserve the detailed features of objects, especially sharp features, while denoising. [0003] Joint bilateral filtering, as an extension of the bilateral filtering technique, has been proven to be an effective feature-preserving method in the field of image processing. This technique has also been suc...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20028G06T5/70
Inventor 郑颖龙李桂清伍世浩
Owner SOUTH CHINA UNIV OF TECH
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