{"id":"https://openalex.org/W3194266351","doi":"https://doi.org/10.1109/tgrs.2021.3104844","title":"DRFD-Net: Using Dual Receptive Field Descriptors for Multitemporal Optical Remote Sensing Image Registration","display_name":"DRFD-Net: Using Dual Receptive Field Descriptors for Multitemporal Optical Remote Sensing Image Registration","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W3194266351","doi":"https://doi.org/10.1109/tgrs.2021.3104844","mag":"3194266351"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2021.3104844","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3104844","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","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/A5008579555","display_name":"Yanan You","orcid":"https://orcid.org/0000-0001-6473-9187"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanan You","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6473-9187","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100695741","display_name":"Chao Li","orcid":"https://orcid.org/0000-0003-1492-5410"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Li","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1492-5410","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101778892","display_name":"Wenli Zhou","orcid":"https://orcid.org/0000-0002-6786-1257"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenli Zhou","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.1884,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.47880589,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"19"},"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":0.9995999932289124,"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":0.9995999932289124,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9962000250816345,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7540374994277954},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7425316572189331},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.7065796852111816},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5395210981369019},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5013515949249268},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.48074865341186523},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46997183561325073},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4107292890548706},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3899037837982178},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.329107403755188}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7540374994277954},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7425316572189331},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.7065796852111816},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5395210981369019},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5013515949249268},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.48074865341186523},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46997183561325073},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4107292890548706},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3899037837982178},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.329107403755188},{"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/tgrs.2021.3104844","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3104844","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G74333972","display_name":null,"funder_award_id":"4214058","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"}],"funders":[{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1491719799","https://openalex.org/W1532362218","https://openalex.org/W1561797649","https://openalex.org/W1677409904","https://openalex.org/W1929856797","https://openalex.org/W1955857676","https://openalex.org/W2003370853","https://openalex.org/W2079700955","https://openalex.org/W2089888558","https://openalex.org/W2095705004","https://openalex.org/W2112796928","https://openalex.org/W2114147217","https://openalex.org/W2117228865","https://openalex.org/W2151103935","https://openalex.org/W2161969291","https://openalex.org/W2163009106","https://openalex.org/W2293670510","https://openalex.org/W2737094507","https://openalex.org/W2737260104","https://openalex.org/W2740578684","https://openalex.org/W2755992512","https://openalex.org/W2760321697","https://openalex.org/W2800324071","https://openalex.org/W2910655660","https://openalex.org/W2913429812","https://openalex.org/W2920582597","https://openalex.org/W2920810773","https://openalex.org/W2921056596","https://openalex.org/W2945116459","https://openalex.org/W2952565170","https://openalex.org/W2953303055","https://openalex.org/W2963406602","https://openalex.org/W2963748588","https://openalex.org/W2973665503","https://openalex.org/W2996158895","https://openalex.org/W3004146378","https://openalex.org/W3010777628","https://openalex.org/W3039458201","https://openalex.org/W3044394888","https://openalex.org/W3047246571","https://openalex.org/W3047443805","https://openalex.org/W3048631361","https://openalex.org/W3058901394","https://openalex.org/W3102692100","https://openalex.org/W3103294617","https://openalex.org/W3103695279","https://openalex.org/W3105146621","https://openalex.org/W3133902755","https://openalex.org/W3140885850","https://openalex.org/W3156593822","https://openalex.org/W3165087808","https://openalex.org/W6674330103","https://openalex.org/W6696973050","https://openalex.org/W6738345448"],"related_works":["https://openalex.org/W3034955165","https://openalex.org/W2094920358","https://openalex.org/W2041448692","https://openalex.org/W2247121321","https://openalex.org/W2391926582","https://openalex.org/W1966831329","https://openalex.org/W1995688991","https://openalex.org/W2020188645","https://openalex.org/W2739923608","https://openalex.org/W2049930962"],"abstract_inverted_index":{"Multitemporal":[0],"optical":[1],"remote":[2],"sensing":[3],"image":[4,14,89,128,169],"registration":[5,15,170],"is":[6,71,137],"still":[7],"a":[8,51,58],"challenging":[9],"problem":[10],"for":[11,119],"current":[12,158],"feature-based":[13],"algorithms":[16],"due":[17],"to":[18,41,75,139],"the":[19,36,43,68,77,80,83,87,94,103,106,126,130,141,147,153,179],"complex":[20],"nonlinear":[21],"discrepancies":[22],"arising":[23],"from":[24,112],"diverse":[25],"factors,":[26],"including":[27],"illumination,":[28],"weather,":[29],"and":[30,108,121,129,166,189,191,201],"surface":[31],"condition":[32],"changes.":[33],"To":[34],"address":[35],"issue,":[37],"this":[38],"article":[39],"attempts":[40],"combine":[42],"dual":[44,95],"receptive":[45],"field":[46],"descriptors":[47,70,81],"(DRFDs)":[48],"constructed":[49],"by":[50],"novel":[52,59],"deep":[53],"convolutional":[54],"network.":[55],"In":[56],"addition,":[57],"inner":[60],"loss":[61],"function":[62],"(ILF)":[63],"that":[64,146],"imposes":[65],"constraints":[66],"on":[67,102,182],"intermediate":[69],"adopted":[72],"in":[73],"order":[74],"consolidate":[76],"distinguishability":[78],"of":[79,86,105,149],"when":[82],"overlapping":[84],"areas":[85],"input":[88],"patches":[90],"are":[91,100,175],"large.":[92],"Subsequently,":[93],"feature":[96,197],"distance":[97],"maps":[98],"(DFDMs)":[99],"built":[101],"basis":[104],"DRFDs":[107,150],"combined":[109],"with":[110,152],"features":[111],"accelerated":[113],"segment":[114],"test":[115],"(FAST)":[116],"key":[117],"points":[118],"efficient":[120],"accurate":[122,177],"correspondence":[123],"establishment":[124],"across":[125],"source":[127],"target":[131],"image.":[132],"Eventually,":[133],"an":[134],"iterative":[135],"algorithm":[136],"proposed":[138],"remove":[140],"possible":[142],"outliers.":[143],"Experiments":[144],"show":[145],"combination":[148],"trained":[151],"ILF":[154],"performs":[155],"better":[156],"than":[157,178],"learnable":[159,183],"local":[160],"descriptors,":[161,184,193],"such":[162,185,194],"as":[163,186,195],"L2-Net,":[164,187],"HardNet,":[165,188],"SOSNet.":[167],"The":[168],"results":[171],"using":[172],"our":[173],"method":[174],"more":[176],"methods":[180],"based":[181],"SOSNet,":[190],"handcrafted":[192],"scale-invariant":[196],"transform":[198],"(SIFT),":[199],"SURF,":[200],"ORB.":[202]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
