Terrain signal photon-extraction algorithm for photon-counting LiDAR based on an adjustable length definition

A signal-extraction algorithm for photon-counting LiDAR is proposed to accurately measure mountainous terrain elevation during daylight. The algorithm exponentially scales distances among photons, employs the shortest path length between photons, and applies a maximum between-class variance method t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Optics express 2024-12, Vol.32 (26), p.46726
Hauptverfasser: Ma, Rujia, Kong, Wei, Liu, Ren, Xue, Ruikai, Huang, Genghua
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 26
container_start_page 46726
container_title Optics express
container_volume 32
creator Ma, Rujia
Kong, Wei
Liu, Ren
Xue, Ruikai
Huang, Genghua
description A signal-extraction algorithm for photon-counting LiDAR is proposed to accurately measure mountainous terrain elevation during daylight. The algorithm exponentially scales distances among photons, employs the shortest path length between photons, and applies a maximum between-class variance method to extract the signals from dense connected point clouds. Simulated and advanced topographic altimeter system (ATLAS) data tests show the algorithm's accuracy surpassing 0.9 in high-relief areas during the day. This method utilizes global and local data consistencies to mitigate terrain fluctuations effects and accurately extract mountainous signals improving signal photon extractions in steep topography under varying background photon-counting rates.
doi_str_mv 10.1364/OE.540437
format Article
fullrecord <record><control><sourceid>crossref</sourceid><recordid>TN_cdi_crossref_primary_10_1364_OE_540437</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_1364_OE_540437</sourcerecordid><originalsourceid>FETCH-LOGICAL-c154t-7fd724e941639ea9192662e3ee9136e4c4cc2012b31264acdccbcec3f97fbdcc3</originalsourceid><addsrcrecordid>eNpNkF9LwzAUxYMoOKcPfoO8-tCZNFljHsesf6BQkPlc0vSmzWiTkWSg396OKQgX7j3cww_OQeiekhVlBX-sy9WaE87EBVpQInnGyZO4_Hdfo5sY94RQLqRYoGkHISjrcLS9UyM-DD55l8FXCkon6x1WY--DTcOEjQ9_f-2PLlnX48o-bz5wqyJ0-GSep9sfY1LtCHgE16cBd2CssyfYLboyaoxw97uX6POl3G3fsqp-fd9uqkzTNU-ZMJ3IOUhOCyZBSSrzosiBAcg5JHDNtc4JzVtG84Ir3WndatDMSGHaWbAlejhzdfAxBjDNIdhJhe-GkubUU1OXzbkn9gMI4l1O</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Terrain signal photon-extraction algorithm for photon-counting LiDAR based on an adjustable length definition</title><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Ma, Rujia ; Kong, Wei ; Liu, Ren ; Xue, Ruikai ; Huang, Genghua</creator><creatorcontrib>Ma, Rujia ; Kong, Wei ; Liu, Ren ; Xue, Ruikai ; Huang, Genghua</creatorcontrib><description>A signal-extraction algorithm for photon-counting LiDAR is proposed to accurately measure mountainous terrain elevation during daylight. The algorithm exponentially scales distances among photons, employs the shortest path length between photons, and applies a maximum between-class variance method to extract the signals from dense connected point clouds. Simulated and advanced topographic altimeter system (ATLAS) data tests show the algorithm's accuracy surpassing 0.9 in high-relief areas during the day. This method utilizes global and local data consistencies to mitigate terrain fluctuations effects and accurately extract mountainous signals improving signal photon extractions in steep topography under varying background photon-counting rates.</description><identifier>ISSN: 1094-4087</identifier><identifier>EISSN: 1094-4087</identifier><identifier>DOI: 10.1364/OE.540437</identifier><language>eng</language><ispartof>Optics express, 2024-12, Vol.32 (26), p.46726</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c154t-7fd724e941639ea9192662e3ee9136e4c4cc2012b31264acdccbcec3f97fbdcc3</cites><orcidid>0000-0003-3759-6613</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,27901,27902</link.rule.ids></links><search><creatorcontrib>Ma, Rujia</creatorcontrib><creatorcontrib>Kong, Wei</creatorcontrib><creatorcontrib>Liu, Ren</creatorcontrib><creatorcontrib>Xue, Ruikai</creatorcontrib><creatorcontrib>Huang, Genghua</creatorcontrib><title>Terrain signal photon-extraction algorithm for photon-counting LiDAR based on an adjustable length definition</title><title>Optics express</title><description>A signal-extraction algorithm for photon-counting LiDAR is proposed to accurately measure mountainous terrain elevation during daylight. The algorithm exponentially scales distances among photons, employs the shortest path length between photons, and applies a maximum between-class variance method to extract the signals from dense connected point clouds. Simulated and advanced topographic altimeter system (ATLAS) data tests show the algorithm's accuracy surpassing 0.9 in high-relief areas during the day. This method utilizes global and local data consistencies to mitigate terrain fluctuations effects and accurately extract mountainous signals improving signal photon extractions in steep topography under varying background photon-counting rates.</description><issn>1094-4087</issn><issn>1094-4087</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNpNkF9LwzAUxYMoOKcPfoO8-tCZNFljHsesf6BQkPlc0vSmzWiTkWSg396OKQgX7j3cww_OQeiekhVlBX-sy9WaE87EBVpQInnGyZO4_Hdfo5sY94RQLqRYoGkHISjrcLS9UyM-DD55l8FXCkon6x1WY--DTcOEjQ9_f-2PLlnX48o-bz5wqyJ0-GSep9sfY1LtCHgE16cBd2CssyfYLboyaoxw97uX6POl3G3fsqp-fd9uqkzTNU-ZMJ3IOUhOCyZBSSrzosiBAcg5JHDNtc4JzVtG84Ir3WndatDMSGHaWbAlejhzdfAxBjDNIdhJhe-GkubUU1OXzbkn9gMI4l1O</recordid><startdate>20241216</startdate><enddate>20241216</enddate><creator>Ma, Rujia</creator><creator>Kong, Wei</creator><creator>Liu, Ren</creator><creator>Xue, Ruikai</creator><creator>Huang, Genghua</creator><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0003-3759-6613</orcidid></search><sort><creationdate>20241216</creationdate><title>Terrain signal photon-extraction algorithm for photon-counting LiDAR based on an adjustable length definition</title><author>Ma, Rujia ; Kong, Wei ; Liu, Ren ; Xue, Ruikai ; Huang, Genghua</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c154t-7fd724e941639ea9192662e3ee9136e4c4cc2012b31264acdccbcec3f97fbdcc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ma, Rujia</creatorcontrib><creatorcontrib>Kong, Wei</creatorcontrib><creatorcontrib>Liu, Ren</creatorcontrib><creatorcontrib>Xue, Ruikai</creatorcontrib><creatorcontrib>Huang, Genghua</creatorcontrib><collection>CrossRef</collection><jtitle>Optics express</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ma, Rujia</au><au>Kong, Wei</au><au>Liu, Ren</au><au>Xue, Ruikai</au><au>Huang, Genghua</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Terrain signal photon-extraction algorithm for photon-counting LiDAR based on an adjustable length definition</atitle><jtitle>Optics express</jtitle><date>2024-12-16</date><risdate>2024</risdate><volume>32</volume><issue>26</issue><spage>46726</spage><pages>46726-</pages><issn>1094-4087</issn><eissn>1094-4087</eissn><abstract>A signal-extraction algorithm for photon-counting LiDAR is proposed to accurately measure mountainous terrain elevation during daylight. The algorithm exponentially scales distances among photons, employs the shortest path length between photons, and applies a maximum between-class variance method to extract the signals from dense connected point clouds. Simulated and advanced topographic altimeter system (ATLAS) data tests show the algorithm's accuracy surpassing 0.9 in high-relief areas during the day. This method utilizes global and local data consistencies to mitigate terrain fluctuations effects and accurately extract mountainous signals improving signal photon extractions in steep topography under varying background photon-counting rates.</abstract><doi>10.1364/OE.540437</doi><orcidid>https://orcid.org/0000-0003-3759-6613</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1094-4087
ispartof Optics express, 2024-12, Vol.32 (26), p.46726
issn 1094-4087
1094-4087
language eng
recordid cdi_crossref_primary_10_1364_OE_540437
source DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
title Terrain signal photon-extraction algorithm for photon-counting LiDAR based on an adjustable length definition
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-02T02%3A57%3A35IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Terrain%20signal%20photon-extraction%20algorithm%20for%20photon-counting%20LiDAR%20based%20on%20an%20adjustable%20length%20definition&rft.jtitle=Optics%20express&rft.au=Ma,%20Rujia&rft.date=2024-12-16&rft.volume=32&rft.issue=26&rft.spage=46726&rft.pages=46726-&rft.issn=1094-4087&rft.eissn=1094-4087&rft_id=info:doi/10.1364/OE.540437&rft_dat=%3Ccrossref%3E10_1364_OE_540437%3C/crossref%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true