{"id":"https://openalex.org/W2963129413","doi":"https://doi.org/10.1109/tgrs.2019.2904659","title":"Spatial\u2013Spectral Fusion by Combining Deep Learning and Variational Model","display_name":"Spatial\u2013Spectral Fusion by Combining Deep Learning and Variational Model","publication_year":2019,"publication_date":"2019-07-22","ids":{"openalex":"https://openalex.org/W2963129413","doi":"https://doi.org/10.1109/tgrs.2019.2904659","mag":"2963129413"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2019.2904659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2019.2904659","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1809.00764","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114374395","display_name":"Huanfeng Shen","orcid":"https://orcid.org/0000-0002-4140-1869"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huanfeng Shen","raw_affiliation_strings":["Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-4140-1869","affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085035578","display_name":"Menghui Jiang","orcid":"https://orcid.org/0000-0003-4814-7514"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Menghui Jiang","raw_affiliation_strings":["School of Resource and Environmental Science, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Resource and Environmental Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089770704","display_name":"Jie Li","orcid":"https://orcid.org/0000-0002-4063-9381"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Li","raw_affiliation_strings":["School of Geodesy and Geomatics, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-4063-9381","affiliations":[{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047576305","display_name":"Qiangqiang Yuan","orcid":"https://orcid.org/0000-0001-7140-2224"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiangqiang Yuan","raw_affiliation_strings":["School of Geodesy and Geomatics, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-7140-2224","affiliations":[{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yanchong Wei","orcid":"https://orcid.org/0000-0003-4766-8959"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yanchong Wei","raw_affiliation_strings":["MCFLY Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4766-8959","affiliations":[{"raw_affiliation_string":"MCFLY Technology, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100673818","display_name":"Liangpei Zhang","orcid":"https://orcid.org/0000-0001-6890-3650"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangpei Zhang","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-6890-3650","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.3775,"has_fulltext":false,"cited_by_count":81,"citation_normalized_percentile":{"value":0.98070083,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"57","issue":"8","first_page":"6169","last_page":"6181"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9988999962806702,"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"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9883999824523926,"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/panchromatic-film","display_name":"Panchromatic film","score":0.8819115161895752},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.7955270409584045},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.7170565724372864},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7077257633209229},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6430132389068604},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.6310968399047852},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.586527943611145},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5587100386619568},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5275040864944458},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46321138739585876},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4351794123649597},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4268777370452881},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4120478928089142},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3400891423225403},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28056347370147705}],"concepts":[{"id":"https://openalex.org/C107445234","wikidata":"https://www.wikidata.org/wiki/Q280995","display_name":"Panchromatic film","level":3,"score":0.8819115161895752},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.7955270409584045},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.7170565724372864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7077257633209229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6430132389068604},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.6310968399047852},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.586527943611145},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5587100386619568},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5275040864944458},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46321138739585876},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4351794123649597},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4268777370452881},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4120478928089142},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3400891423225403},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28056347370147705},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2019.2904659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2019.2904659","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"},{"id":"pmh:oai:arXiv.org:1809.00764","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.00764","pdf_url":"https://arxiv.org/pdf/1809.00764","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1809.00764","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.00764","pdf_url":"https://arxiv.org/pdf/1809.00764","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6145440980","display_name":null,"funder_award_id":"41701400","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7565599351","display_name":null,"funder_award_id":"61671334","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W106317687","https://openalex.org/W935139217","https://openalex.org/W1247035941","https://openalex.org/W1522046140","https://openalex.org/W1553305639","https://openalex.org/W1654063000","https://openalex.org/W1943127271","https://openalex.org/W1969210895","https://openalex.org/W2001800591","https://openalex.org/W2002345587","https://openalex.org/W2004913087","https://openalex.org/W2009820353","https://openalex.org/W2011830145","https://openalex.org/W2014316959","https://openalex.org/W2032275874","https://openalex.org/W2036825992","https://openalex.org/W2039247168","https://openalex.org/W2047757202","https://openalex.org/W2054440797","https://openalex.org/W2064366277","https://openalex.org/W2103428240","https://openalex.org/W2124743705","https://openalex.org/W2124952510","https://openalex.org/W2149720806","https://openalex.org/W2164306391","https://openalex.org/W2171108951","https://openalex.org/W2171211028","https://openalex.org/W2171627515","https://openalex.org/W2194775991","https://openalex.org/W2295976914","https://openalex.org/W2326587421","https://openalex.org/W2414009677","https://openalex.org/W2462592242","https://openalex.org/W2468704697","https://openalex.org/W2494274259","https://openalex.org/W2508457857","https://openalex.org/W2514340250","https://openalex.org/W2524927183","https://openalex.org/W2584156879","https://openalex.org/W2600626704","https://openalex.org/W2613155248","https://openalex.org/W2619662254","https://openalex.org/W2755186337","https://openalex.org/W2761333220","https://openalex.org/W2775207294","https://openalex.org/W2788008270","https://openalex.org/W2792111852","https://openalex.org/W2796464444","https://openalex.org/W2803825432","https://openalex.org/W2806155925","https://openalex.org/W2806865914","https://openalex.org/W2951070760","https://openalex.org/W2951572255","https://openalex.org/W2963183385","https://openalex.org/W2963442801","https://openalex.org/W2963583038","https://openalex.org/W3098435832","https://openalex.org/W3103964896","https://openalex.org/W3105234146","https://openalex.org/W3122817556","https://openalex.org/W4285719527","https://openalex.org/W6604338981","https://openalex.org/W6624640001","https://openalex.org/W6628238970","https://openalex.org/W6631230401","https://openalex.org/W6633088995"],"related_works":["https://openalex.org/W1930929277","https://openalex.org/W2158394102","https://openalex.org/W2361746014","https://openalex.org/W1502637513","https://openalex.org/W2124952510","https://openalex.org/W2375311607","https://openalex.org/W2022261651","https://openalex.org/W2011962637","https://openalex.org/W2163677711","https://openalex.org/W2036727360"],"abstract_inverted_index":{"In":[0],"the":[1,6,11,27,36,60,64,81,84,88,98,112,129,137,142],"field":[2],"of":[3,40,63,83,146],"spatial\u2013spectral":[4,41],"fusion,":[5],"variational":[7,33,74,114],"model-based":[8],"methods":[9,15],"and":[10,97,118],"deep":[12,28,49],"learning":[13],"(DL)-based":[14],"are":[16,76],"state-of-the-art":[17],"approaches.":[18],"This":[19],"paper":[20],"presents":[21],"a":[22,32,48],"fusion":[23,104,113,131,148],"method":[24,132],"that":[25,128],"combines":[26],"neural":[29,52],"network":[30,53],"with":[31],"model":[34],"for":[35],"most":[37],"common":[38],"case":[39],"fusion:":[42],"panchromatic":[43],"(PAN)/multispectral":[44],"(MS)":[45],"fusion.":[46],"Specifically,":[47],"residual":[50],"convolutional":[51],"(CNN)":[54],"is":[55,133],"first":[56],"trained":[57],"to":[58,79,135],"learn":[59],"gradient":[61,99],"features":[62],"high":[65],"spatial":[66,91],"resolution":[67,92],"multispectral":[68,93],"image":[69,72,94],"(HR-MS).":[70],"The":[71],"observation":[73],"models":[75],"then":[77,107],"formulated":[78],"describe":[80],"relationships":[82],"ideal":[85],"fused":[86],"image,":[87,96],"observed":[89],"low":[90],"(LR-MS)":[95],"priors":[100],"learned":[101],"before.":[102],"Then,":[103],"result":[105],"can":[106],"be":[108],"obtained":[109],"by":[110],"solving":[111],"model.":[115],"Both":[116],"quantitative":[117],"visual":[119],"assessments":[120],"on":[121],"high-quality":[122],"images":[123],"from":[124],"various":[125],"sources":[126],"demonstrate":[127],"proposed":[130],"superior":[134],"all":[136],"mainstream":[138],"algorithms":[139],"included":[140],"in":[141,144],"comparison,":[143],"terms":[145],"overall":[147],"accuracy.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":14}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-07-30T00:00:00"}