{"id":"https://openalex.org/W2953583213","doi":"https://doi.org/10.1109/lgrs.2019.2922347","title":"Infrared Small Target Detection Using Homogeneity-Weighted Local Contrast Measure","display_name":"Infrared Small Target Detection Using Homogeneity-Weighted Local Contrast Measure","publication_year":2019,"publication_date":"2019-07-07","ids":{"openalex":"https://openalex.org/W2953583213","doi":"https://doi.org/10.1109/lgrs.2019.2922347","mag":"2953583213"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2019.2922347","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2922347","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101841142","display_name":"Peng Du","orcid":"https://orcid.org/0000-0003-0053-8057"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peng Du","raw_affiliation_strings":["Institute of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075133420","display_name":"Askar Hamdulla","orcid":"https://orcid.org/0000-0002-2321-308X"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Askar Hamdulla","raw_affiliation_strings":["Institute of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China","institution_ids":["https://openalex.org/I96908189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101841142"],"corresponding_institution_ids":["https://openalex.org/I96908189"],"apc_list":null,"apc_paid":null,"fwci":70.9112,"has_fulltext":false,"cited_by_count":92,"citation_normalized_percentile":{"value":0.99810255,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"17","issue":"3","first_page":"514","last_page":"518"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.8952580094337463},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7597974538803101},{"id":"https://openalex.org/keywords/homogeneity","display_name":"Homogeneity (statistics)","score":0.7432221174240112},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.674277126789093},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6245587468147278},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5489544868469238},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4868294596672058},{"id":"https://openalex.org/keywords/target-acquisition","display_name":"Target acquisition","score":0.45403003692626953},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.43102535605430603},{"id":"https://openalex.org/keywords/infrared","display_name":"Infrared","score":0.4260184168815613},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.4190451502799988},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.1536942422389984},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.147597074508667},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.13346049189567566},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10373231768608093},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07572495937347412},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.07111850380897522}],"concepts":[{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.8952580094337463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7597974538803101},{"id":"https://openalex.org/C142259097","wikidata":"https://www.wikidata.org/wiki/Q5891314","display_name":"Homogeneity (statistics)","level":2,"score":0.7432221174240112},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.674277126789093},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6245587468147278},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5489544868469238},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4868294596672058},{"id":"https://openalex.org/C2779726219","wikidata":"https://www.wikidata.org/wiki/Q7685884","display_name":"Target acquisition","level":2,"score":0.45403003692626953},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.43102535605430603},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.4260184168815613},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.4190451502799988},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.1536942422389984},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.147597074508667},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.13346049189567566},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10373231768608093},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07572495937347412},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.07111850380897522},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2019.2922347","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2922347","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4132105060","display_name":null,"funder_award_id":"61563049","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1976526581","https://openalex.org/W1978993121","https://openalex.org/W2006851788","https://openalex.org/W2041560658","https://openalex.org/W2041646550","https://openalex.org/W2048643133","https://openalex.org/W2067173181","https://openalex.org/W2080197848","https://openalex.org/W2291670705","https://openalex.org/W2327560060","https://openalex.org/W2341998679","https://openalex.org/W2540854551","https://openalex.org/W2594017825","https://openalex.org/W2790021535","https://openalex.org/W2792463169"],"related_works":["https://openalex.org/W2095116634","https://openalex.org/W1598209139","https://openalex.org/W2308064968","https://openalex.org/W2052706302","https://openalex.org/W1506254081","https://openalex.org/W2089867446","https://openalex.org/W1994690353","https://openalex.org/W2056886394","https://openalex.org/W1965897874","https://openalex.org/W2951217132"],"abstract_inverted_index":{"Detecting":[0],"small":[1,23,47],"targets":[2],"in":[3,12,164],"infrared":[4],"(IR)":[5],"image":[6,111],"sequences":[7],"is":[8,39,122,156],"an":[9,45,136],"important":[10],"task":[11],"IR":[13,46],"guidance":[14],"systems.":[15],"The":[16,124],"clutter":[17],"of":[18,63,83,94,166],"complex":[19,37,105],"backgrounds":[20,38],"often":[21],"submerges":[22],"targets,":[24],"making":[25],"detection":[26,30,49],"difficult.":[27],"Achieving":[28],"high":[29],"and":[31,86,89,130,171],"low":[32],"false":[33],"alarm":[34],"rates":[35],"with":[36,114],"a":[40,115],"primary":[41],"problem.":[42],"We":[43,134],"propose":[44],"target":[48,101,129,140],"method":[50,76,108,155],"using":[51],"our":[52,75,153],"new":[53],"homogeneity-weighted":[54],"local":[55,80],"contrast":[56,81],"measure":[57],"(HWLCM).":[58],"Inspired":[59],"by":[60],"the":[61,64,79,84,90,95,100,104,120,127,146,167],"ability":[62],"human":[65],"visual":[66],"system":[67],"(HVS)":[68],"to":[69,77,98,139,143],"determine":[70],"saliency":[71],"characteristics,":[72],"we":[73],"implement":[74],"use":[78],"features":[82],"central":[85],"surrounding":[87,96],"regions":[88,97],"weighted":[91],"homogeneity":[92],"characteristics":[93],"enhance":[99],"while":[102],"suppressing":[103],"background.":[106],"Our":[107,148],"divides":[109],"each":[110],"into":[112],"blocks":[113],"sliding":[116],"window":[117],"for":[118],"which":[119],"HWLCM":[121,125],"calculated.":[123],"enhances":[126],"actual":[128],"suppresses":[131],"interference":[132],"simultaneously.":[133],"apply":[135],"adaptive":[137],"threshold":[138],"region":[141],"extraction":[142],"further":[144],"refine":[145],"results.":[147],"experimental":[149],"results":[150],"show":[151],"that":[152],"proposed":[154],"more":[157],"effective":[158],"than":[159],"six":[160],"comparable":[161],"methods,":[162],"especially":[163],"terms":[165],"signal-to-clutter":[168],"gain":[169],"(SCRG)":[170],"background":[172],"suppression":[173],"factor":[174],"(BSF)":[175],"indicators.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":28},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
