{"id":"https://openalex.org/W4292970248","doi":"https://doi.org/10.1109/lgrs.2022.3200373","title":"Adaptive Registration for Optical and SAR Images With a Scale-Constrained Matching Method","display_name":"Adaptive Registration for Optical and SAR Images With a Scale-Constrained Matching Method","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4292970248","doi":"https://doi.org/10.1109/lgrs.2022.3200373"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2022.3200373","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3200373","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/A5103228896","display_name":"Liang Yuan","orcid":"https://orcid.org/0000-0001-5494-1250"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuan Liang","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101972883","display_name":"Tao Su","orcid":"https://orcid.org/0000-0003-1529-4198"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Su","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065504878","display_name":"Ning Lv","orcid":"https://orcid.org/0000-0003-4091-714X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Lv","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100705677","display_name":"Jiao Guo","orcid":"https://orcid.org/0000-0003-4362-0683"},"institutions":[{"id":"https://openalex.org/I89652312","display_name":"Northwest A&F University","ror":"https://ror.org/0051rme32","country_code":"CN","type":"education","lineage":["https://openalex.org/I89652312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiao Guo","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, China","institution_ids":["https://openalex.org/I89652312"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074330724","display_name":"Jiangtao Liu","orcid":"https://orcid.org/0000-0002-6176-1538"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangtao Liu","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103228896"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.5094,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.63772686,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9976000189781189,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.707482635974884},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6481755971908569},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6345556974411011},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.6232738494873047},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5754148960113525},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.5627104043960571},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5477638840675354},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47579988837242126},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4610942602157593},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44633162021636963},{"id":"https://openalex.org/keywords/sobel-operator","display_name":"Sobel operator","score":0.4325975179672241},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.4213855564594269},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2935575246810913},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.23086097836494446},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.22786375880241394}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.707482635974884},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6481755971908569},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6345556974411011},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.6232738494873047},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5754148960113525},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.5627104043960571},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5477638840675354},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47579988837242126},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4610942602157593},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44633162021636963},{"id":"https://openalex.org/C30703548","wikidata":"https://www.wikidata.org/wiki/Q1757673","display_name":"Sobel operator","level":5,"score":0.4325975179672241},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.4213855564594269},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2935575246810913},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.23086097836494446},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.22786375880241394},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2022.3200373","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3200373","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":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1980113665","https://openalex.org/W2030233108","https://openalex.org/W2047243114","https://openalex.org/W2085261163","https://openalex.org/W2111308925","https://openalex.org/W2144123711","https://openalex.org/W2145072179","https://openalex.org/W2147555557","https://openalex.org/W2151103935","https://openalex.org/W2177274842","https://openalex.org/W2559871160","https://openalex.org/W2792119716","https://openalex.org/W3049515841","https://openalex.org/W3087985223","https://openalex.org/W3156527559"],"related_works":["https://openalex.org/W3034955165","https://openalex.org/W2362890552","https://openalex.org/W2392642780","https://openalex.org/W1985441784","https://openalex.org/W2378303881","https://openalex.org/W55503292","https://openalex.org/W2094920358","https://openalex.org/W2041448692","https://openalex.org/W2247121321","https://openalex.org/W2391926582"],"abstract_inverted_index":{"Images":[0],"registration":[1,25,46,57],"for":[2,27,44,92,97],"optical":[3,28,60,94],"and":[4,29,61,163,181,200,204],"synthetic":[5],"aperture":[6],"radar":[7],"(SAR)":[8],"is":[9,47,67,111,132,152],"a":[10,48,54,101,140],"key":[11,49],"of":[12,23,70,75,79,135,176,196],"multi-sensor":[13],"images":[14,33,63],"analysis.":[15],"And":[16],"parameters":[17],"selection":[18],"affects":[19],"the":[20,24,71,81,84,90,93,98,107,115,118,121,136,174,194,197],"final":[21],"result":[22],"algorithms":[26],"SAR":[30,62,99],"images.":[31],"For":[32],"obtained":[34],"by":[35,125,144],"different":[36,72],"sensors,":[37],"how":[38],"to":[39,88,113],"choose":[40],"an":[41],"appropriate":[42],"parameter":[43,55],"accurate":[45],"problem.":[50],"In":[51,117],"this":[52],"letter,":[53],"adaptive":[56,103,122],"algorithm":[58,82,167,199],"between":[59],"based":[64,105],"on":[65,106],"SIFT":[66],"proposed.":[68,153],"Because":[69],"imaging":[73],"mechanisms":[74],"these":[76],"two":[77,159],"kinds":[78],"images,":[80],"uses":[83],"multiscale":[85],"Sobel":[86],"operator":[87,104],"calculate":[89,114],"gradient":[91],"image,":[95,100],"while":[96],"new":[102],"neighborhood":[108],"pixel":[109],"value":[110,123],"proposed":[112,169],"gradient.":[116],"feature":[119,161],"extraction,":[120],"estimated":[124],"constant":[126],"false":[127],"alarm":[128],"rate":[129,180],"(CFAR)":[130],"detection":[131],"used":[133],"instead":[134],"fixed":[137],"threshold.":[138],"Finally,":[139],"matching":[141,179],"method":[142,192],"constrained":[143],"image":[145,164],"size":[146],"scaling":[147],"(Scale-Constrained":[148],"Fast":[149],"Sample":[150],"Consensus)":[151],"The":[154,166,186],"evaluation":[155],"was":[156],"designed":[157],"in":[158,173],"aspects:":[160],"extraction":[162],"registration.":[165],"we":[168],"shows":[170],"excellent":[171],"performances":[172],"aspects":[175],"repeatability,":[177],"correct":[178],"root":[182],"mean":[183],"square":[184],"error.":[185],"experimental":[187],"results":[188],"show":[189],"that":[190],"our":[191],"maintains":[193],"performance":[195],"original":[198],"has":[201],"some":[202],"optimization":[203],"breakthrough.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}