An adaptive continuous threshold wavelet denoising method for LiDAR echo signal

Dezhi Zheng; Tianchi Qu; Chun Hu; Shijia Lu; Zhongxiang Li; Guanyu Yang; Xiaojun Yang

doi:10.1063/10.0034398

An adaptive continuous threshold wavelet denoising method for LiDAR echo signal

Dezhi Zheng, Tianchi Qu, Chun Hu^*, Shijia Lu^*, Zhongxiang Li, Guanyu Yang, Xiaojun Yang

^*此作品的通讯作者

前沿交叉科学研究院

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

ARTICLE HIGHLIGHTS • Adaptive continuous thresholding, which dynamically adjusts the threshold according to the number of wavelet decomposition layers, provides variable thresholds in different layers to effectively differentiate between signal and noise. • The continuous threshold function has good continuity and minimizes the deviation of the estimated wavelet coefficients from the actual values, which ensures the accuracy and effectiveness of the denoising process. • By denoising real measured LiDAR echo signals, it is demonstrated that this method enhancing the denoising capability while maintaining the integrity of the original signal details.

源语言	英语
文章编号	023006
期刊	Nanotechnology and Precision Engineering
卷	8
期	2
DOI	https://doi.org/10.1063/10.0034398
出版状态	已出版 - 1 6月 2025

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10.1063/10.0034398

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Zheng, D., Qu, T., Hu, C., Lu, S., Li, Z., Yang, G., & Yang, X. (2025). An adaptive continuous threshold wavelet denoising method for LiDAR echo signal. Nanotechnology and Precision Engineering, 8(2), 文章 023006. https://doi.org/10.1063/10.0034398

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title = "An adaptive continuous threshold wavelet denoising method for LiDAR echo signal",

abstract = "ARTICLE HIGHLIGHTS • Adaptive continuous thresholding, which dynamically adjusts the threshold according to the number of wavelet decomposition layers, provides variable thresholds in different layers to effectively differentiate between signal and noise. • The continuous threshold function has good continuity and minimizes the deviation of the estimated wavelet coefficients from the actual values, which ensures the accuracy and effectiveness of the denoising process. • By denoising real measured LiDAR echo signals, it is demonstrated that this method enhancing the denoising capability while maintaining the integrity of the original signal details.",

keywords = "Adaptive thresholding, Echo signal, Single-photon LiDAR, Wavelet transform",

author = "Dezhi Zheng and Tianchi Qu and Chun Hu and Shijia Lu and Zhongxiang Li and Guanyu Yang and Xiaojun Yang",

note = "Publisher Copyright: {\textcopyright} 2024 Author(s).",

year = "2025",

month = jun,

day = "1",

doi = "10.1063/10.0034398",

language = "English",

volume = "8",

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T1 - An adaptive continuous threshold wavelet denoising method for LiDAR echo signal

AU - Zheng, Dezhi

AU - Qu, Tianchi

AU - Hu, Chun

AU - Lu, Shijia

AU - Li, Zhongxiang

AU - Yang, Guanyu

AU - Yang, Xiaojun

PY - 2025/6/1

Y1 - 2025/6/1

N2 - ARTICLE HIGHLIGHTS • Adaptive continuous thresholding, which dynamically adjusts the threshold according to the number of wavelet decomposition layers, provides variable thresholds in different layers to effectively differentiate between signal and noise. • The continuous threshold function has good continuity and minimizes the deviation of the estimated wavelet coefficients from the actual values, which ensures the accuracy and effectiveness of the denoising process. • By denoising real measured LiDAR echo signals, it is demonstrated that this method enhancing the denoising capability while maintaining the integrity of the original signal details.

AB - ARTICLE HIGHLIGHTS • Adaptive continuous thresholding, which dynamically adjusts the threshold according to the number of wavelet decomposition layers, provides variable thresholds in different layers to effectively differentiate between signal and noise. • The continuous threshold function has good continuity and minimizes the deviation of the estimated wavelet coefficients from the actual values, which ensures the accuracy and effectiveness of the denoising process. • By denoising real measured LiDAR echo signals, it is demonstrated that this method enhancing the denoising capability while maintaining the integrity of the original signal details.

KW - Adaptive thresholding

KW - Echo signal

KW - Single-photon LiDAR

KW - Wavelet transform

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DO - 10.1063/10.0034398

M3 - Article

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SN - 1672-6030

VL - 8

JO - Nanotechnology and Precision Engineering

JF - Nanotechnology and Precision Engineering

IS - 2

M1 - 023006

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An adaptive continuous threshold wavelet denoising method for LiDAR echo signal

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