Denoising of the multi-slit streak tube imaging LiDAR system using a faster non-local mean method

Wenhao Li, Shangwei Guo, Yu Zhai, Fei Liu, Zhengchao Lai, Shaokun Han*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Combined with the characteristic of the multi-slit streak tube imaging LiDAR (MS-STIL) system where the imaging areas corresponding to each slit do not interfere with each other, we denoised the streak images by an improved fast non-local mean filtering algorithm. Experiments were performed to investigate the effectiveness of the method. The experimental results show that the spatial resolution of the system is improved from 22 to 16 mm; the relative distance error is reduced by an average of 22.76%; and the intensity accuracy improved significantly when the distance is 10 m. Additionally, the overall denoising effect is comprehensively verified by long-range target imaging. The mean square error of the reconstructed depth image and intensity image are reduced from 0.0836, 0.0067 to 0.0433, 0.0037, respectively. The applicability of the proposed method was verified through comparative experiments in different environments.

Original languageEnglish
Pages (from-to)10520-10528
Number of pages9
JournalApplied Optics
Volume60
Issue number34
DOIs
Publication statusPublished - 1 Dec 2021

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