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Complex scene photon counting laser radar point cloud denoising algorithm based on multi-peak Gaussian fitting

A technology for photon counting points and complex scenes, which is applied in computing, image data processing, still image data retrieval, etc., can solve problems such as the complexity of the actual environment, and achieve the effects of improving processing efficiency, accurately identifying noise, and rationally designing

Active Publication Date: 2020-08-11
曹彬才
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Problems solved by technology

However, due to the extremely high detection sensitivity of returning photons, the actual environment of this type of system is very complex, and there are background sunlight and multipath effects, resulting in a large number of useless noise points in the 3D point cloud

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  • Complex scene photon counting laser radar point cloud denoising algorithm based on multi-peak Gaussian fitting
  • Complex scene photon counting laser radar point cloud denoising algorithm based on multi-peak Gaussian fitting
  • Complex scene photon counting laser radar point cloud denoising algorithm based on multi-peak Gaussian fitting

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Embodiment Construction

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0022] see Figure 1-8 , the present invention provides a technical solution: a complex scene photon counting lidar point cloud denoising algorithm based on multi-peak Gaussian fitting, the basic idea is that the signal points in the photon counting point cloud are denser than the noise points in spatial distribution , even when the measurement conditions are complex and the density of the point cloud is not uniform, the noise points are theoretically more spa...

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Abstract

The invention discloses a complex scene photon counting laser radar point cloud denoising algorithm based on multi-peak Gaussian fitting in the technical field of laser radar point cloud data denoising. The basic idea is that signal points in the photon counting point cloud are denser than noise points in spatial distribution. Even if the measurement condition is relatively complex, when the density of the point clouds is not uniform, theoretically, noise points are sparse; the method is based on point cloud density histogram features. Fitting multi-peak distribution through a Gaussian function; the method can adaptively calculate the noise and signal separation threshold to achieve the purpose of accurate denoising, is suitable for complex conditions of uneven noise density, and can adaptively and accurately calculate the denoising threshold, so that the noise is more accurately recognized, and the purpose of improving the photon counting laser radar point cloud data processing efficiency is achieved.

Description

technical field [0001] The invention relates to the technical field of denoising laser radar point cloud data, in particular to a denoising algorithm capable of processing photon counting laser radar point cloud data in complex environments. Background technique [0002] Lidar is a measurement technology that integrates laser, global positioning system, inertial navigation system and other technologies, and aims to actively detect the three-dimensional information of the target. It has the characteristics of high precision and fast speed, and is widely used in terrain survey and engineering precision survey , Shallow sea bathymetry, vegetation forest estimation and other occasions. Most of the existing lidar systems use linear detection methods, and obtain the complete pulse information on the detection path through full waveform sampling. The advantage is that it is beneficial to multiple target classification and environmental parameter inversion. Water body parameters ca...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T5/40G06F16/51G01S7/48
CPCG06T5/40G06F16/51G01S7/48G06T2207/10028G06T2207/10044G06T5/70Y02A90/10
Inventor 曹彬才方勇江振治高力胡海彦
Owner 曹彬才
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