A method and system for denoising imaging of lidar data by geiger apd array

CN122923005APending Publication Date: 2026-10-16HUAZHONG UNIV OF SCI & TECH
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Patent Information

Application Number
CN202510412253.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-03
Publication Date
2026-10-16

AI Technical Summary

Technical Problem

然而基于点云滤波的方法和基于波形识别的方法想要达到较好的去噪成像效果,往往涉及大量特殊算子的计算,计算复杂度较高

Benefits of technology

[0030] 1. This invention provides a denoising imaging method for Geiger APD array lidar data. Considering that the noise distribution of Geiger APD array lidar data generally has high temporal stability, this invention performs noise distribution estimation every preset time interval. The noise distribution of the lidar data is estimated in advance by curve fitting the frequency distribution of the global time count values ​​of the lidar data sequence S to be denoised or the lidar data sequence S' collected within a preset time interval before the current lidar data to be denoised. Then, denoising imaging is performed on the lidar data sequence S based on the pre-estimated noise distribution, resulting in good denoising imaging performance. This invention does not involve the calculation of special operators, has low computational complexity, and only requires one noise distribution estimation within a certain time interval to meet the denoising requirements for that time interval, greatly reducing computational overhead. At the same time, this invention does not require training with large-scale and diverse training datasets, resulting in high real-time performance. Based on this, this invention can achieve good denoising imaging performance with low computational complexity while meeting real-time requirements.

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Abstract

The application discloses a kind of Geiger APD array laser radar data denoising imaging method and system, belong to laser radar technical field;Considering that the noise distribution of Geiger APD array laser radar data in general scene has higher stability in time, the application carries out noise distribution estimation every interval preset time period, then based on the noise distribution estimated in advance, laser radar data sequence is denoised and imaged, and the denoising imaging effect is better.The application does not involve the calculation of special operator, and the calculation complexity is lower, and only needs to carry out noise distribution estimation in a period of time to meet the denoising demand in this time period, greatly reduces the computing overhead;At the same time, the application also does not need to use large-scale and diversified training data set for training, and the real-time performance is higher;Based on this, the application can meet the real-time requirement while achieving better denoising imaging effect with lower calculation complexity.
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