Infrared Small Target Detection Based on Adaptive Region Growing Algorithm With Iterative Threshold Analysis

Existing infrared (IR) small target detection algorithms often lack adaptability in complex scenes and heavily rely on parameter configurations. To address this limitation, we propose a novel IR small target detection method based on adaptive region growing algorithm with iterative threshold analysi...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on geoscience and remote sensing Vol. 62; pp. 1 - 15
Main Authors Li, Yongsong, Li, Zhengzhou, Guo, Zhiwei, Siddique, Abubakar, Liu, Yuchuan, Yu, Keping
Format Journal Article
LanguageEnglish
Published New York IEEE 2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptability
Adaptive algorithms
Adaptive region growing algorithm
Algorithms
Clutter
Filtering algorithms
Image edge detection
Image segmentation
infrared (IR) imaging
Infrared analysis
Iterative algorithms
iterative threshold analysis
Object detection
Remote sensing
small target detection
Target detection
Online AccessGet full text

Cover

Abstract Existing infrared (IR) small target detection algorithms often lack adaptability in complex scenes and heavily rely on parameter configurations. To address this limitation, we propose a novel IR small target detection method based on adaptive region growing algorithm with iterative threshold analysis that leverages the homogenous compactness of the small target and discontinuity with its surroundings. Initially, the image undergoes adaptive splitting into multiple regions using an automatic seeded region growing (ASRG) algorithm, eliminating the need for preassigned seed points. Next, the segmentation results at each threshold are utilized to calculate the relative residual map (RRM) and local dissimilarity map (LDM), contributing to the selection of the optimal threshold. Finally, RRM and LDM corresponding to the optimal threshold are integrated to accurately characterize the small target signal while effectively removing background clutter. The experimental results show that the proposed method is effective in clutter removal and small target detection in diverse complex scenes and is robust to the shape and size of targets.
AbstractList Existing infrared (IR) small target detection algorithms often lack adaptability in complex scenes and heavily rely on parameter configurations. To address this limitation, we propose a novel IR small target detection method based on adaptive region growing algorithm with iterative threshold analysis that leverages the homogenous compactness of the small target and discontinuity with its surroundings. Initially, the image undergoes adaptive splitting into multiple regions using an automatic seeded region growing (ASRG) algorithm, eliminating the need for preassigned seed points. Next, the segmentation results at each threshold are utilized to calculate the relative residual map (RRM) and local dissimilarity map (LDM), contributing to the selection of the optimal threshold. Finally, RRM and LDM corresponding to the optimal threshold are integrated to accurately characterize the small target signal while effectively removing background clutter. The experimental results show that the proposed method is effective in clutter removal and small target detection in diverse complex scenes and is robust to the shape and size of targets.
Author Guo, Zhiwei
Li, Zhengzhou
Siddique, Abubakar
Liu, Yuchuan
Yu, Keping
Li, Yongsong
Author_xml – sequence: 1
  givenname: Yongsong
  orcidid: 0000-0002-5955-2999
  surname: Li
  fullname: Li, Yongsong
  email: liyongsong@ctbu.edu.cn
  organization: School of Artificial Intelligence, Chongqing Technology and Business University, Chongqing, China
– sequence: 2
  givenname: Zhengzhou
  orcidid: 0000-0001-5275-1728
  surname: Li
  fullname: Li, Zhengzhou
  email: lizhengzhou@cqu.edu.cn
  organization: School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China
– sequence: 3
  givenname: Zhiwei
  orcidid: 0000-0001-8868-6913
  surname: Guo
  fullname: Guo, Zhiwei
  email: zwguo@ctbu.edu.cn
  organization: School of Artificial Intelligence, Chongqing Technology and Business University, Chongqing, China
– sequence: 4
  givenname: Abubakar
  orcidid: 0009-0000-4131-9665
  surname: Siddique
  fullname: Siddique, Abubakar
  email: abubakar@cqu.edu.cn
  organization: School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China
– sequence: 5
  givenname: Yuchuan
  orcidid: 0000-0003-3010-7653
  surname: Liu
  fullname: Liu, Yuchuan
  email: liuyc@cqust.edu.cn
  organization: School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing, China
– sequence: 6
  givenname: Keping
  orcidid: 0000-0001-5735-2507
  surname: Yu
  fullname: Yu, Keping
  email: keping.yu@ieee.org
  organization: Graduate School of Science and Engineering, Hosei University, Tokyo, Japan
BookMark eNpNkE9Lw0AQxRdRsK1-AMHDgufU_ZNsssdYtRYKQhvxGDab2TQlTeruVum3N7E9eJkZeO8NM78xumy7FhC6o2RKKZGP2Xy1njLCwinnsQhZdIFGNIqSgIgwvEQjQqUIWCLZNRo7tyWEhhGNR6hZtMYqCyVe71TT4EzZCjx-Bg_a112Ln5TrxX5IS7X39TfgFVSDMLfdT91WOG2qztZ-s8OffcULD1b9-bKNBbfpmhKnrWqOrnY36MqoxsHtuU_Qx-tLNnsLlu_zxSxdBpqFwgcMpNZGqTgmMkqYFIaaRJbcxImQcak1LQqugZlChrwoIOFFqYkQSWlAUyr4BD2c9u5t93UA5_Ntd7D9ES7nJOr_jiMxuOjJpW3nnAWT7229U_aYU5IPUPMBaj5Azc9Q-8z9KVMDwD9_KJJIMP4L7_12ow
CODEN IGRSD2
Cites_doi 10.1016/j.infrared.2018.01.032
10.1016/j.infrared.2019.05.010
10.1016/j.patcog.2016.04.002
10.1109/TGRS.2019.2911513
10.1109/TGRS.2020.3044958
10.1109/LGRS.2020.3004978
10.1109/LGRS.2021.3080986
10.1109/TGRS.2023.3244784
10.1016/j.infrared.2019.06.003
10.1109/TGRS.2021.3074289
10.1016/j.infrared.2021.103657
10.1016/j.patcog.2008.10.013
10.1109/TAES.2020.3024391
10.1364/AO.54.004689
10.1109/TGRS.2021.3068465
10.1109/TAES.2022.3189336
10.1109/TGRS.2023.3276175
10.1117/1.2724874
10.1016/j.jag.2021.102669
10.1016/j.neucom.2020.08.065
10.1109/TGRS.2022.3163173
10.3390/rs12121963
10.1109/tgrs.2020.3040221
10.1109/LGRS.2022.3196433
10.1016/j.sigpro.2020.107727
10.1109/JSTARS.2017.2700023
10.1109/LGRS.2020.3003267
10.1109/TIP.2013.2281420
10.1109/JSTARS.2021.3115637
10.1109/TGRS.2023.3246565
10.1109/LGRS.2019.2912989
10.1109/TGRS.2020.3022069
10.1016/j.infrared.2021.103893
10.1109/TGRS.2017.2660879
10.1109/TPAMI.2008.15
10.1016/j.dsp.2020.102949
10.1109/TGRS.2023.3242960
10.1109/LGRS.2021.3050828
10.1109/TGRS.2023.3276995
10.1109/TIM.2021.3080385
10.1109/TGRS.2013.2242477
10.1109/LGRS.2016.2616416
10.1109/LGRS.2021.3070984
10.1109/TGRS.2012.2190079
10.1109/JSTARS.2018.2828317
10.1109/LGRS.2020.3047524
10.1016/j.patcog.2009.12.023
10.1109/LGRS.2017.2711047
10.1016/j.optlastec.2012.08.009
10.1109/JSTARS.2022.3200380
10.1109/TGRS.2016.2538295
10.1016/j.patcog.2020.107729
ContentType Journal Article
Copyright Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024
Copyright_xml – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024
DBID 97E
RIA
RIE
AAYXX
CITATION
7UA
8FD
C1K
F1W
FR3
H8D
H96
KR7
L.G
L7M
DOI 10.1109/TGRS.2024.3376425
DatabaseName IEEE All-Society Periodicals Package (ASPP) 2005-present
IEEE All-Society Periodicals Package (ASPP) 1998-Present
IEEE Electronic Library (IEL)
CrossRef
Water Resources Abstracts
Technology Research Database
Environmental Sciences and Pollution Management
ASFA: Aquatic Sciences and Fisheries Abstracts
Engineering Research Database
Aerospace Database
Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources
Civil Engineering Abstracts
Aquatic Science & Fisheries Abstracts (ASFA) Professional
Advanced Technologies Database with Aerospace
DatabaseTitle CrossRef
Aerospace Database
Civil Engineering Abstracts
Aquatic Science & Fisheries Abstracts (ASFA) Professional
Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources
Technology Research Database
ASFA: Aquatic Sciences and Fisheries Abstracts
Engineering Research Database
Advanced Technologies Database with Aerospace
Water Resources Abstracts
Environmental Sciences and Pollution Management
DatabaseTitleList
Aerospace Database
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
Physics
EISSN 1558-0644
EndPage 15
ExternalDocumentID 10_1109_TGRS_2024_3376425
10468562
Genre orig-research
GrantInformation_xml – fundername: National Natural Science Foundation of China
  grantid: 61675036
  funderid: 10.13039/501100001809
– fundername: Open Foundation of Chongqing Key Laboratory for Oil and Gas Production Safety and Risk Control
  grantid: cqsrc202113
– fundername: Science and Technology Research Project of Chongqing Municipal Education Commission of China
  grantid: KJQN202200827
– fundername: High-Level Talent Research Start-Up Fund of Chongqing Technology and Business University (CTBU)
  grantid: 5156022
  funderid: 10.13039/501100004500
GroupedDBID -~X
0R~
29I
4.4
5GY
5VS
6IK
97E
AAJGR
AASAJ
AAYOK
ABQJQ
ABVLG
ACGFO
ACGFS
ACIWK
ACNCT
AENEX
AETIX
AFRAH
AI.
AIBXA
AKJIK
ALLEH
ALMA_UNASSIGNED_HOLDINGS
ASUFR
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CS3
DU5
EBS
EJD
F5P
HZ~
H~9
IBMZZ
ICLAB
IFIPE
IFJZH
IPLJI
JAVBF
LAI
M43
O9-
OCL
P2P
RIA
RIE
RIG
RNS
RXW
TAE
TN5
VH1
XFK
Y6R
AAYXX
CITATION
7UA
8FD
C1K
F1W
FR3
H8D
H96
KR7
L.G
L7M
ID FETCH-LOGICAL-c246t-2e9ccfaa770958296f1f89d3f78697dcc1bb3ce2fb943bbe83bdc0668dfec1163
IEDL.DBID RIE
ISSN 0196-2892
IngestDate Thu Oct 10 19:57:42 EDT 2024
Fri Aug 23 02:59:06 EDT 2024
Wed Jun 26 19:38:48 EDT 2024
IsPeerReviewed true
IsScholarly true
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c246t-2e9ccfaa770958296f1f89d3f78697dcc1bb3ce2fb943bbe83bdc0668dfec1163
ORCID 0000-0001-8868-6913
0000-0003-3010-7653
0000-0002-5955-2999
0000-0001-5735-2507
0009-0000-4131-9665
0000-0001-5275-1728
PQID 3055177566
PQPubID 85465
PageCount 15
ParticipantIDs crossref_primary_10_1109_TGRS_2024_3376425
proquest_journals_3055177566
ieee_primary_10468562
PublicationCentury 2000
PublicationDate 20240000
2024-00-00
20240101
PublicationDateYYYYMMDD 2024-01-01
PublicationDate_xml – year: 2024
  text: 20240000
PublicationDecade 2020
PublicationPlace New York
PublicationPlace_xml – name: New York
PublicationTitle IEEE transactions on geoscience and remote sensing
PublicationTitleAbbrev TGRS
PublicationYear 2024
Publisher IEEE
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml – name: IEEE
– name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References ref13
ref12
ref15
ref14
ref52
ref11
ref10
ref17
ref16
ref19
ref18
ref51
ref50
ref46
ref45
ref48
ref47
ref42
ref41
ref44
ref43
ref49
ref8
ref7
ref9
ref4
ref3
ref6
ref5
ref40
ref35
ref34
ref37
ref36
ref31
ref30
ref33
ref32
ref2
ref1
ref39
ref38
ref24
ref23
ref26
ref25
ref20
ref22
ref21
ref28
ref27
ref29
References_xml – ident: ref26
  doi: 10.1016/j.infrared.2018.01.032
– ident: ref7
  doi: 10.1016/j.infrared.2019.05.010
– ident: ref30
  doi: 10.1016/j.patcog.2016.04.002
– ident: ref5
  doi: 10.1109/TGRS.2019.2911513
– ident: ref14
  doi: 10.1109/TGRS.2020.3044958
– ident: ref32
  doi: 10.1109/LGRS.2020.3004978
– ident: ref45
  doi: 10.1109/LGRS.2021.3080986
– ident: ref1
  doi: 10.1109/TGRS.2023.3244784
– ident: ref28
  doi: 10.1016/j.infrared.2019.06.003
– ident: ref41
  doi: 10.1109/TGRS.2021.3074289
– ident: ref20
  doi: 10.1016/j.infrared.2021.103657
– ident: ref49
  doi: 10.1016/j.patcog.2008.10.013
– ident: ref13
  doi: 10.1109/TAES.2020.3024391
– ident: ref17
  doi: 10.1364/AO.54.004689
– ident: ref24
  doi: 10.1109/TGRS.2021.3068465
– ident: ref3
  doi: 10.1109/TAES.2022.3189336
– ident: ref48
  doi: 10.1109/TGRS.2023.3276175
– ident: ref44
  doi: 10.1117/1.2724874
– ident: ref52
  doi: 10.1016/j.jag.2021.102669
– ident: ref23
  doi: 10.1016/j.neucom.2020.08.065
– ident: ref11
  doi: 10.1109/TGRS.2022.3163173
– ident: ref15
  doi: 10.3390/rs12121963
– ident: ref21
  doi: 10.1109/tgrs.2020.3040221
– ident: ref38
  doi: 10.1109/LGRS.2022.3196433
– ident: ref27
  doi: 10.1016/j.sigpro.2020.107727
– ident: ref22
  doi: 10.1109/JSTARS.2017.2700023
– ident: ref31
  doi: 10.1109/LGRS.2020.3003267
– ident: ref4
  doi: 10.1109/TIP.2013.2281420
– ident: ref51
  doi: 10.1109/JSTARS.2021.3115637
– ident: ref47
  doi: 10.1109/TGRS.2023.3246565
– ident: ref39
  doi: 10.1109/LGRS.2019.2912989
– ident: ref8
  doi: 10.1109/TGRS.2020.3022069
– ident: ref16
  doi: 10.1016/j.infrared.2021.103893
– ident: ref6
  doi: 10.1109/TGRS.2017.2660879
– ident: ref40
  doi: 10.1109/TPAMI.2008.15
– ident: ref50
  doi: 10.1016/j.dsp.2020.102949
– ident: ref33
  doi: 10.1109/TGRS.2023.3242960
– ident: ref12
  doi: 10.1109/LGRS.2021.3050828
– ident: ref10
  doi: 10.1109/TGRS.2023.3276995
– ident: ref43
  doi: 10.1109/TIM.2021.3080385
– ident: ref29
  doi: 10.1109/TGRS.2013.2242477
– ident: ref46
  doi: 10.1109/LGRS.2016.2616416
– ident: ref36
  doi: 10.1109/LGRS.2021.3070984
– ident: ref42
  doi: 10.1109/TGRS.2012.2190079
– ident: ref9
  doi: 10.1109/JSTARS.2018.2828317
– ident: ref34
  doi: 10.1109/LGRS.2020.3047524
– ident: ref19
  doi: 10.1016/j.patcog.2009.12.023
– ident: ref35
  doi: 10.1109/LGRS.2017.2711047
– ident: ref18
  doi: 10.1016/j.optlastec.2012.08.009
– ident: ref37
  doi: 10.1109/JSTARS.2022.3200380
– ident: ref25
  doi: 10.1109/TGRS.2016.2538295
– ident: ref2
  doi: 10.1016/j.patcog.2020.107729
SSID ssj0014517
Score 2.5491052
Snippet Existing infrared (IR) small target detection algorithms often lack adaptability in complex scenes and heavily rely on parameter configurations. To address...
SourceID proquest
crossref
ieee
SourceType Aggregation Database
Publisher
StartPage 1
SubjectTerms Adaptability
Adaptive algorithms
Adaptive region growing algorithm
Algorithms
Clutter
Filtering algorithms
Image edge detection
Image segmentation
infrared (IR) imaging
Infrared analysis
Iterative algorithms
iterative threshold analysis
Object detection
Remote sensing
small target detection
Target detection
Title Infrared Small Target Detection Based on Adaptive Region Growing Algorithm With Iterative Threshold Analysis
URI https://ieeexplore.ieee.org/document/10468562
https://www.proquest.com/docview/3055177566
Volume 62
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LS8QwEA4qCHrwLa4vcvAkdLdJ06Y5rm8FPeiKeyt5qrh2Zbd78dc7SbuyKIKXkkMaQmYyj8w3MwgdcWITRg2PYidoxChxkVAmBoJocEByCTrb5zvf3mVXj-ymn_abZPWQC2OtDeAz2_bDEMs3Qz3xT2UdH4_MUy9x57kQdbLWd8iApaTJjc4i8CJoE8Iksej0Lu8fwBWkrJ3AfWK-LfaMEgpdVX6J4qBfLlbR3XRnNazkrT2pVFt__ija-O-tr6GVxtLE3Zo11tGcLTfQ8kz9wQ20GPCferyJBtelG3ksOn54l4MB7gWAOD6zVYBqlfgEtJ3BMOga-eFFJL63HsqML8GPh8Vwd_A8HL1WL-_4Cb74OlRr9vN6wC1jH-TC0wIoW-jx4rx3ehU1jRgiTVlWRdQKrZ2UnINBllOROeJyYRLH80xwozVRKtGWOiVYopTNE2U02DK5cVYTsPi20UI5LO0OwonhXIJkM3kaM5YyKVgqwa2JlckkJbaFjqeUKT7qehtF8FNiUXgyFp6MRUPGFtryJz0zsT7kFtqfErNoruS48KXNCOdgvu7-8dseWvKr1w8s-2ihGk3sAZgclToMrPYF9sLSkw
link.rule.ids 315,783,787,799,4033,27937,27938,27939,55088
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1Lb9QwEB5VrRBwKFCKWCitD5yQso0dJ46Py6PdhXYPbSp6i_ykFdtstZu98OsZO1m0AiH1EvngJJa_sWfG880Y4L2gLuPMiiT1kiWcUZ9IbVMExKADUirU2SHf-XxajK_41-v8uk9Wj7kwzrlIPnPD0IyxfDs3q3BUdhzikWUedtydPBgWXbrWn6ABz2mfHV0k6EewPohJU3lcnV5cojPI-DDDFcXDxdgbaijeq_LPZhw1zMkzmK7H1hFLfg5XrR6aX3-VbXzw4J_Dbm9rklEnHC9gyzV78HSjAuEePIoMULN8CbNJ4xeBjU4u79RsRqpIESefXRvJWg35iPrOEmyMrLoPmyS5cIHMTE7Rk8ePkdHsx3xx297cke_4JJNYrzn0q1BeliHMRdYlUPbh6uRL9Wmc9FcxJIbxok2Yk8Z4pYRAk6xksvDUl9JmXpSFFNYYqnVmHPNa8kxrV2baGrRmSuudoWjzvYLtZt6410AyK4RC8GyZp5znXEmeK3RsUm0LxagbwIc1MvV9V3Gjjp5KKusAYx1grHsYB7AfZnqjYzfJAzhYg1n3i3JZh-JmVAg0YN_857UjeDyuzs_qs8n021t4Ev7UHbccwHa7WLl3aIC0-jCK3W8muNXg
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Infrared+Small+Target+Detection+Based+on+Adaptive+Region+Growing+Algorithm+With+Iterative+Threshold+Analysis&rft.jtitle=IEEE+transactions+on+geoscience+and+remote+sensing&rft.au=Li%2C+Yongsong&rft.au=Li%2C+Zhengzhou&rft.au=Guo%2C+Zhiwei&rft.au=Siddique%2C+Abubakar&rft.date=2024&rft.issn=0196-2892&rft.eissn=1558-0644&rft.volume=62&rft.spage=1&rft.epage=15&rft_id=info:doi/10.1109%2FTGRS.2024.3376425&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_TGRS_2024_3376425
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0196-2892&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0196-2892&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0196-2892&client=summon