scholarly journals Voxel-based spatial elongation filtering method for airborne single-photon LiDAR data

2020 ◽  
Vol 28 (3) ◽  
pp. 3922
Author(s):  
Tong Luo ◽  
Deying Chen ◽  
Zhaodong Chen ◽  
Zhiwei Dong ◽  
Wentao Wu ◽  
...  
Keyword(s):  
Single Photon ◽  
Lidar Data ◽  
Filtering Method

A Novel Voxel-based Spatial Elongation Filtering Method for Single-Photon Lidar Data

2019 ◽  
Author(s):  
Tong Luo ◽  
Rongwei Fan ◽  
Zhaodong Chen ◽  
Zhiwei Dong ◽  
Wentao Wu
Keyword(s):  
Single Photon ◽  
Lidar Data ◽  
Filtering Method

scholarly journals An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation

2016 ◽  
Vol 8 (6) ◽  
pp. 501 ◽  
Author(s):  
Wuming Zhang ◽  
Jianbo Qi ◽  
Peng Wan ◽  
Hongtao Wang ◽  
Donghui Xie ◽  
...  
Keyword(s):  
Airborne Lidar ◽  
Lidar Data ◽  
Data Filtering ◽  
Cloth Simulation ◽  
Filtering Method ◽  
Airborne Lidar Data

scholarly journals Real-time 3D reconstruction from single-photon lidar data using plug-and-play point cloud denoisers

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Julián Tachella ◽  
Yoann Altmann ◽  
Nicolas Mellado ◽  
Aongus McCarthy ◽  
Rachael Tobin ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Real Time ◽  
Single Photon ◽  
Three Dimensional ◽  
Lidar Data ◽  
Computational Framework ◽  
Processing Times ◽  
Outdoor Scenes ◽  
3D Scene ◽  
Time Required

Abstract Single-photon lidar has emerged as a prime candidate technology for depth imaging through challenging environments. Until now, a major limitation has been the significant amount of time required for the analysis of the recorded data. Here we show a new computational framework for real-time three-dimensional (3D) scene reconstruction from single-photon data. By combining statistical models with highly scalable computational tools from the computer graphics community, we demonstrate 3D reconstruction of complex outdoor scenes with processing times of the order of 20 ms, where the lidar data was acquired in broad daylight from distances up to 320 metres. The proposed method can handle an unknown number of surfaces in each pixel, allowing for target detection and imaging through cluttered scenes. This enables robust, real-time target reconstruction of complex moving scenes, paving the way for single-photon lidar at video rates for practical 3D imaging applications.

Fast Classification and Depth Estimation for Multispectral Single-Photon LiDAR Data

2021 ◽  
Author(s):  
Mohamed Amir Alaa Belmekki ◽  
Stephen McLaughlin ◽  
Abderrahim Halimi
Keyword(s):  
Single Photon ◽  
Depth Estimation ◽  
Lidar Data ◽  
Fast Classification

Exploring Building Data from Multispectral and Single-Photon Lidar Systems

2020 ◽  
Author(s):  
Lingli Zhu ◽  
Juha Hyyppä ◽  
Juho-pekka Virtanen ◽  
Xiaowei Yu ◽  
Harri Kaartinen
Keyword(s):  
Noise Level ◽  
Single Photon ◽  
Lidar Data ◽  
Vector Data ◽  
Advantages And Disadvantages ◽  
The Individual ◽  
Intensity Density ◽  
Density Resolution ◽  
Resolution Data ◽  
Better Than

This paper investigated building data from multispectral and single-photon Lidar systems. The multispectral datasets from the individual channels and fused channels were explored. The multispectral and single-photon Lidar data were compared across multiple aspects: the data acquisition geometry, number of echoes, intensity, density, resolution, data defects, noise level, and the absolute and relative accuracy. In addition, we explored the performance of the multispectral and single-photon data for roof plane detection for eight complex/stylish buildings to investigate the suitability of these data for 3D building reconstruction. The building data from the single-photon and multispectral Lidar systems were evaluated with respect to the reference building vector data with an accuracy of better than 5 cm. The advantages and disadvantages of both technologies and their applications in the urban building environment are discussed.

First Evaluation on Single Photon-Sensitive Lidar Data

2016 ◽  
Vol 82 (7) ◽  
pp. 455-463 ◽  
Author(s):  
Qinghua Li ◽  
John Degnan ◽  
Terence Barrett ◽  
Jie Shan
Keyword(s):  
Single Photon ◽  
Lidar Data

Joint surface detection and depth estimation from single-photon Lidar data using ensemble estimators

2021 ◽  
Author(s):  
K. Drummond ◽  
S. McLaughlin ◽  
Y. Altmann ◽  
A. Pawlikowska ◽  
R. Lamb
Keyword(s):  
Single Photon ◽  
Depth Estimation ◽  
Joint Surface ◽  
Lidar Data ◽  
Surface Detection

Restoration of Sparse Multispectral Single Photon Lidar Data

2020 ◽  
Author(s):  
Songmao Chen ◽  
Wei Hao ◽  
Xiuqin Su ◽  
Zhenyang Zhang ◽  
Shuchao Wang ◽  
...  
Keyword(s):  
Single Photon ◽  
Lidar Data
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