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

^*Corresponding author for this work

Advanced Research Institute of Multidisciplinary Science

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

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.

Original language	English
Article number	023006
Journal	Nanotechnology and Precision Engineering
Volume	8
Issue number	2
DOIs	http://doi.org/10.1063/10.0034398
Publication status	Published - 1 Jun 2025

Keywords

Adaptive thresholding
Echo signal
Single-photon LiDAR
Wavelet transform

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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",

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doi = "10.1063/10.0034398",

language = "English",

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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

UR - http://www.scopus.com/pages/publications/105000302564

U2 - 10.1063/10.0034398

DO - 10.1063/10.0034398

M3 - Article

AN - SCOPUS:105000302564

SN - 1672-6030

VL - 8

JO - Nanotechnology and Precision Engineering

JF - Nanotechnology and Precision Engineering

IS - 2

M1 - 023006

ER -

An adaptive continuous threshold wavelet denoising method for LiDAR echo signal

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Keywords

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