Infrared small target detection based on local multidirectional gradient

Aiming at the problem of low detection rate of small infrared target under complex background and heavy clutter interference, an infrared small target detection method based on local multidirectional gradient is proposed. Firstly, Laplace operator is used to sharpen the image and enhance the target....

Full description

Saved in:
Bibliographic Details
Main Authors: Qiu, Guoqing, Yang, Haijing, Wei, Yating, Wang, Yantao, Luo, Pan
Format: Conference Proceeding
Language:English
Subjects:
Clutter
Feature extraction
Image edge detection
Image segmentation
Infrared small target
Local multidirectional gradient
Object detection
Sea level
Target detection
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 5683
container_issue
container_start_page 5679
container_title
container_volume
creator Qiu, Guoqing
Yang, Haijing
Wei, Yating
Wang, Yantao
Luo, Pan
description Aiming at the problem of low detection rate of small infrared target under complex background and heavy clutter interference, an infrared small target detection method based on local multidirectional gradient is proposed. Firstly, Laplace operator is used to sharpen the image and enhance the target. Then, the local multidirectional gradient function is redefined by the gradient direction feature analysis of the image. And it improves the anti-jamming ability for strong clutter. Finally, the real target is extracted by adaptive threshold segmentation. The experimental results show that the method can effectively improve the target detection ability under complex background and strong clutter interference.
doi_str_mv 10.1109/CAC48633.2019.8997030
format conference_proceeding
fullrecord <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_8997030</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8997030</ieee_id><sourcerecordid>8997030</sourcerecordid><originalsourceid>FETCH-LOGICAL-i203t-7940bcb58cc2919c464a0150c418f6ee004e9b5e55d8df7315486c6a37b1a6dd3</originalsourceid><addsrcrecordid>eNotj81KAzEUhaMgWGufQIR5gRnvzd8kyzKoLRTc6LpkkjslkplKJi58ewfa1TmcDw58jD0jNIhgX7ptJ40WouGAtjHWtiDghj1gyw1KsFLcshXXxtRghblnm3n-BgAuUCoJK7bbT0N2mUI1jy6lqrh8olIFKuRLPE9V7-YFLiWdvUvV-JtKDDFf6DKcsguRpvLI7gaXZtpcc82-3l4_u119-Hjfd9tDHTmIUrdWQu97ZbznFq2XWjpABV6iGTQRgCTbK1IqmDC0AtWi57UTbY9OhyDW7OnyG4no-JPj6PLf8Sou_gGNak1o</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Infrared small target detection based on local multidirectional gradient</title><source>IEEE Xplore All Conference Series</source><creator>Qiu, Guoqing ; Yang, Haijing ; Wei, Yating ; Wang, Yantao ; Luo, Pan</creator><creatorcontrib>Qiu, Guoqing ; Yang, Haijing ; Wei, Yating ; Wang, Yantao ; Luo, Pan</creatorcontrib><description>Aiming at the problem of low detection rate of small infrared target under complex background and heavy clutter interference, an infrared small target detection method based on local multidirectional gradient is proposed. Firstly, Laplace operator is used to sharpen the image and enhance the target. Then, the local multidirectional gradient function is redefined by the gradient direction feature analysis of the image. And it improves the anti-jamming ability for strong clutter. Finally, the real target is extracted by adaptive threshold segmentation. The experimental results show that the method can effectively improve the target detection ability under complex background and strong clutter interference.</description><identifier>EISSN: 2688-0938</identifier><identifier>EISBN: 1728140943</identifier><identifier>EISBN: 9781728140940</identifier><identifier>DOI: 10.1109/CAC48633.2019.8997030</identifier><language>eng</language><publisher>IEEE</publisher><subject>Clutter ; Feature extraction ; Image edge detection ; Image segmentation ; Infrared small target ; Local multidirectional gradient ; Object detection ; Sea level ; Target detection</subject><ispartof>2019 Chinese Automation Congress (CAC), 2019, p.5679-5683</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8997030$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,23930,23931,25140,27925,54555,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8997030$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Qiu, Guoqing</creatorcontrib><creatorcontrib>Yang, Haijing</creatorcontrib><creatorcontrib>Wei, Yating</creatorcontrib><creatorcontrib>Wang, Yantao</creatorcontrib><creatorcontrib>Luo, Pan</creatorcontrib><title>Infrared small target detection based on local multidirectional gradient</title><title>2019 Chinese Automation Congress (CAC)</title><addtitle>CAC</addtitle><description>Aiming at the problem of low detection rate of small infrared target under complex background and heavy clutter interference, an infrared small target detection method based on local multidirectional gradient is proposed. Firstly, Laplace operator is used to sharpen the image and enhance the target. Then, the local multidirectional gradient function is redefined by the gradient direction feature analysis of the image. And it improves the anti-jamming ability for strong clutter. Finally, the real target is extracted by adaptive threshold segmentation. The experimental results show that the method can effectively improve the target detection ability under complex background and strong clutter interference.</description><subject>Clutter</subject><subject>Feature extraction</subject><subject>Image edge detection</subject><subject>Image segmentation</subject><subject>Infrared small target</subject><subject>Local multidirectional gradient</subject><subject>Object detection</subject><subject>Sea level</subject><subject>Target detection</subject><issn>2688-0938</issn><isbn>1728140943</isbn><isbn>9781728140940</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2019</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj81KAzEUhaMgWGufQIR5gRnvzd8kyzKoLRTc6LpkkjslkplKJi58ewfa1TmcDw58jD0jNIhgX7ptJ40WouGAtjHWtiDghj1gyw1KsFLcshXXxtRghblnm3n-BgAuUCoJK7bbT0N2mUI1jy6lqrh8olIFKuRLPE9V7-YFLiWdvUvV-JtKDDFf6DKcsguRpvLI7gaXZtpcc82-3l4_u119-Hjfd9tDHTmIUrdWQu97ZbznFq2XWjpABV6iGTQRgCTbK1IqmDC0AtWi57UTbY9OhyDW7OnyG4no-JPj6PLf8Sou_gGNak1o</recordid><startdate>201911</startdate><enddate>201911</enddate><creator>Qiu, Guoqing</creator><creator>Yang, Haijing</creator><creator>Wei, Yating</creator><creator>Wang, Yantao</creator><creator>Luo, Pan</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201911</creationdate><title>Infrared small target detection based on local multidirectional gradient</title><author>Qiu, Guoqing ; Yang, Haijing ; Wei, Yating ; Wang, Yantao ; Luo, Pan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i203t-7940bcb58cc2919c464a0150c418f6ee004e9b5e55d8df7315486c6a37b1a6dd3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Clutter</topic><topic>Feature extraction</topic><topic>Image edge detection</topic><topic>Image segmentation</topic><topic>Infrared small target</topic><topic>Local multidirectional gradient</topic><topic>Object detection</topic><topic>Sea level</topic><topic>Target detection</topic><toplevel>online_resources</toplevel><creatorcontrib>Qiu, Guoqing</creatorcontrib><creatorcontrib>Yang, Haijing</creatorcontrib><creatorcontrib>Wei, Yating</creatorcontrib><creatorcontrib>Wang, Yantao</creatorcontrib><creatorcontrib>Luo, Pan</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Qiu, Guoqing</au><au>Yang, Haijing</au><au>Wei, Yating</au><au>Wang, Yantao</au><au>Luo, Pan</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Infrared small target detection based on local multidirectional gradient</atitle><btitle>2019 Chinese Automation Congress (CAC)</btitle><stitle>CAC</stitle><date>2019-11</date><risdate>2019</risdate><spage>5679</spage><epage>5683</epage><pages>5679-5683</pages><eissn>2688-0938</eissn><eisbn>1728140943</eisbn><eisbn>9781728140940</eisbn><abstract>Aiming at the problem of low detection rate of small infrared target under complex background and heavy clutter interference, an infrared small target detection method based on local multidirectional gradient is proposed. Firstly, Laplace operator is used to sharpen the image and enhance the target. Then, the local multidirectional gradient function is redefined by the gradient direction feature analysis of the image. And it improves the anti-jamming ability for strong clutter. Finally, the real target is extracted by adaptive threshold segmentation. The experimental results show that the method can effectively improve the target detection ability under complex background and strong clutter interference.</abstract><pub>IEEE</pub><doi>10.1109/CAC48633.2019.8997030</doi><tpages>5</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier EISSN: 2688-0938
ispartof 2019 Chinese Automation Congress (CAC), 2019, p.5679-5683
issn 2688-0938
language eng
recordid cdi_ieee_primary_8997030
source IEEE Xplore All Conference Series
subjects Clutter
Feature extraction
Image edge detection
Image segmentation
Infrared small target
Local multidirectional gradient
Object detection
Sea level
Target detection
title Infrared small target detection based on local multidirectional gradient
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T20%3A41%3A58IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Infrared%20small%20target%20detection%20based%20on%20local%20multidirectional%20gradient&rft.btitle=2019%20Chinese%20Automation%20Congress%20(CAC)&rft.au=Qiu,%20Guoqing&rft.date=2019-11&rft.spage=5679&rft.epage=5683&rft.pages=5679-5683&rft.eissn=2688-0938&rft_id=info:doi/10.1109/CAC48633.2019.8997030&rft.eisbn=1728140943&rft.eisbn_list=9781728140940&rft_dat=%3Cieee_CHZPO%3E8997030%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i203t-7940bcb58cc2919c464a0150c418f6ee004e9b5e55d8df7315486c6a37b1a6dd3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=8997030&rfr_iscdi=true