A COMPARISON OF TWO DIFFERENT APPROACHES OF POINT CLOUD CLASSIFICATION BASED ON FULL-WAVEFORM LIDAR DATA

In this paper, two different point cloud classification approaches were applied based on the full-waveform LiDAR data. At the beginning, based on the full-waveform LiDAR data, we decomposed the backscattered pulse waveform and abstracted each component in the waveform after the pre-processing of noi...

Full description

Bibliographic Details
Main Authors: J.-H. Wang, C.-R. Li, L.-L. Tang, M. Zhou, J.-M. Li
Format: Article
Language:English
Published: Copernicus Publications 2012-07-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B3/179/2012/isprsarchives-XXXIX-B3-179-2012.pdf
_version_ 1828765799944290304
author J.-H. Wang
J.-H. Wang
C.-R. Li
L.-L. Tang
M. Zhou
J.-M. Li
author_facet J.-H. Wang
J.-H. Wang
C.-R. Li
L.-L. Tang
M. Zhou
J.-M. Li
author_sort J.-H. Wang
collection DOAJ
description In this paper, two different point cloud classification approaches were applied based on the full-waveform LiDAR data. At the beginning, based on the full-waveform LiDAR data, we decomposed the backscattered pulse waveform and abstracted each component in the waveform after the pre-processing of noise detection and waveform smoothing. And by the time flag of each component acquired in the decomposition procedure we calculated the three dimension coordination of the component. Then the components’ waveform properties, including amplitude, width and cross-section, were uniformed respectively and formed the Amplitude/Width/Section space. Then two different approaches were applied to classify the points. First, we selected certain targets and trained the parameters, after that, by the supervised classification way we segmented the study area point. On the other hand, we apply the IHSL colour transform to the above space to find a new space, RGB colour space, which has a uniform distinguishability among the parameters and contains the whole information of each component in Amplitude/Width/Section space. Then the fuzzy C-means algorithm is applied to the derived RGB space to complete the LiDAR point classification procedure. By comparing the two different segmentation results, which may of substantial importance for further targets detection and identification, a brief discussion and conclusion were brought out for further research and study.
first_indexed 2024-12-11T06:54:29Z
format Article
id doaj.art-74038a534df942d090ce6d2bb2dbab8f
institution Directory Open Access Journal
issn 1682-1750
2194-9034
language English
last_indexed 2024-12-11T06:54:29Z
publishDate 2012-07-01
publisher Copernicus Publications
record_format Article
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
spelling doaj.art-74038a534df942d090ce6d2bb2dbab8f2022-12-22T01:16:48ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342012-07-01XXXIX-B317918210.5194/isprsarchives-XXXIX-B3-179-2012A COMPARISON OF TWO DIFFERENT APPROACHES OF POINT CLOUD CLASSIFICATION BASED ON FULL-WAVEFORM LIDAR DATAJ.-H. Wang0J.-H. Wang1C.-R. Li2L.-L. Tang3M. Zhou4J.-M. Li5Academy of Opto-Electronics, Chinese Academy of Sciences, Dengzhuang South Road, Beijing, ChinaThe Graduate University of Chinese Academy of Sciences, Yuquan Road, Beijing, ChinaAcademy of Opto-Electronics, Chinese Academy of Sciences, Dengzhuang South Road, Beijing, ChinaAcademy of Opto-Electronics, Chinese Academy of Sciences, Dengzhuang South Road, Beijing, ChinaAcademy of Opto-Electronics, Chinese Academy of Sciences, Dengzhuang South Road, Beijing, ChinaAcademy of Opto-Electronics, Chinese Academy of Sciences, Dengzhuang South Road, Beijing, ChinaIn this paper, two different point cloud classification approaches were applied based on the full-waveform LiDAR data. At the beginning, based on the full-waveform LiDAR data, we decomposed the backscattered pulse waveform and abstracted each component in the waveform after the pre-processing of noise detection and waveform smoothing. And by the time flag of each component acquired in the decomposition procedure we calculated the three dimension coordination of the component. Then the components’ waveform properties, including amplitude, width and cross-section, were uniformed respectively and formed the Amplitude/Width/Section space. Then two different approaches were applied to classify the points. First, we selected certain targets and trained the parameters, after that, by the supervised classification way we segmented the study area point. On the other hand, we apply the IHSL colour transform to the above space to find a new space, RGB colour space, which has a uniform distinguishability among the parameters and contains the whole information of each component in Amplitude/Width/Section space. Then the fuzzy C-means algorithm is applied to the derived RGB space to complete the LiDAR point classification procedure. By comparing the two different segmentation results, which may of substantial importance for further targets detection and identification, a brief discussion and conclusion were brought out for further research and study.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B3/179/2012/isprsarchives-XXXIX-B3-179-2012.pdf
spellingShingle J.-H. Wang
J.-H. Wang
C.-R. Li
L.-L. Tang
M. Zhou
J.-M. Li
A COMPARISON OF TWO DIFFERENT APPROACHES OF POINT CLOUD CLASSIFICATION BASED ON FULL-WAVEFORM LIDAR DATA
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title A COMPARISON OF TWO DIFFERENT APPROACHES OF POINT CLOUD CLASSIFICATION BASED ON FULL-WAVEFORM LIDAR DATA
title_full A COMPARISON OF TWO DIFFERENT APPROACHES OF POINT CLOUD CLASSIFICATION BASED ON FULL-WAVEFORM LIDAR DATA
title_fullStr A COMPARISON OF TWO DIFFERENT APPROACHES OF POINT CLOUD CLASSIFICATION BASED ON FULL-WAVEFORM LIDAR DATA
title_full_unstemmed A COMPARISON OF TWO DIFFERENT APPROACHES OF POINT CLOUD CLASSIFICATION BASED ON FULL-WAVEFORM LIDAR DATA
title_short A COMPARISON OF TWO DIFFERENT APPROACHES OF POINT CLOUD CLASSIFICATION BASED ON FULL-WAVEFORM LIDAR DATA
title_sort comparison of two different approaches of point cloud classification based on full waveform lidar data
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B3/179/2012/isprsarchives-XXXIX-B3-179-2012.pdf
work_keys_str_mv AT jhwang acomparisonoftwodifferentapproachesofpointcloudclassificationbasedonfullwaveformlidardata
AT jhwang acomparisonoftwodifferentapproachesofpointcloudclassificationbasedonfullwaveformlidardata
AT crli acomparisonoftwodifferentapproachesofpointcloudclassificationbasedonfullwaveformlidardata
AT lltang acomparisonoftwodifferentapproachesofpointcloudclassificationbasedonfullwaveformlidardata
AT mzhou acomparisonoftwodifferentapproachesofpointcloudclassificationbasedonfullwaveformlidardata
AT jmli acomparisonoftwodifferentapproachesofpointcloudclassificationbasedonfullwaveformlidardata
AT jhwang comparisonoftwodifferentapproachesofpointcloudclassificationbasedonfullwaveformlidardata
AT jhwang comparisonoftwodifferentapproachesofpointcloudclassificationbasedonfullwaveformlidardata
AT crli comparisonoftwodifferentapproachesofpointcloudclassificationbasedonfullwaveformlidardata
AT lltang comparisonoftwodifferentapproachesofpointcloudclassificationbasedonfullwaveformlidardata
AT mzhou comparisonoftwodifferentapproachesofpointcloudclassificationbasedonfullwaveformlidardata
AT jmli comparisonoftwodifferentapproachesofpointcloudclassificationbasedonfullwaveformlidardata