{"id":"https://openalex.org/W3134743586","doi":"https://doi.org/10.1109/tgrs.2020.3046321","title":"A Band Divide-and-Conquer Multispectral and Hyperspectral Image Fusion Method","display_name":"A Band Divide-and-Conquer Multispectral and Hyperspectral Image Fusion Method","publication_year":2021,"publication_date":"2021-02-25","ids":{"openalex":"https://openalex.org/W3134743586","doi":"https://doi.org/10.1109/tgrs.2020.3046321","mag":"3134743586"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.3046321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3046321","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/A5050009113","display_name":"Weiwei Sun","orcid":"https://orcid.org/0000-0003-3399-7858"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Sun","raw_affiliation_strings":["Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, China"],"raw_orcid":"https://orcid.org/0000-0003-3399-7858","affiliations":[{"raw_affiliation_string":"Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016525205","display_name":"Kai Ren","orcid":"https://orcid.org/0000-0003-4704-5743"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Ren","raw_affiliation_strings":["Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018282808","display_name":"Xiangchao Meng","orcid":"https://orcid.org/0000-0002-7405-3143"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangchao Meng","raw_affiliation_strings":["Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China"],"raw_orcid":"https://orcid.org/0000-0002-7405-3143","affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102663415","display_name":"Chenchao Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I2799486974","display_name":"China Geological Survey","ror":"https://ror.org/04wtq2305","country_code":"CN","type":"other","lineage":["https://openalex.org/I2799486974"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenchao Xiao","raw_affiliation_strings":["China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing, China","institution_ids":["https://openalex.org/I2799486974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074018705","display_name":"Gang Yang","orcid":"https://orcid.org/0000-0002-7001-2037"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Yang","raw_affiliation_strings":["Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, China"],"raw_orcid":"https://orcid.org/0000-0002-7001-2037","affiliations":[{"raw_affiliation_string":"Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036030486","display_name":"Jiangtao Peng","orcid":"https://orcid.org/0000-0002-4759-0584"},"institutions":[{"id":"https://openalex.org/I75900474","display_name":"Hubei University","ror":"https://ror.org/03a60m280","country_code":"CN","type":"education","lineage":["https://openalex.org/I75900474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangtao Peng","raw_affiliation_strings":["Hubei Key Laboratory of Applied Mathematics, Faculty of Mathematics and Statistics, Hubei University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-4759-0584","affiliations":[{"raw_affiliation_string":"Hubei Key Laboratory of Applied Mathematics, Faculty of Mathematics and Statistics, Hubei University, Wuhan, China","institution_ids":["https://openalex.org/I75900474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.9729,"has_fulltext":false,"cited_by_count":75,"citation_normalized_percentile":{"value":0.9778075,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"13"},"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":0.9993000030517578,"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":0.9758999943733215,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8255324363708496},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.7665621638298035},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6155564785003662},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.6006175875663757},{"id":"https://openalex.org/keywords/spectral-bands","display_name":"Spectral bands","score":0.5927630662918091},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5645409226417542},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4960375726222992},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4770978093147278},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4294772744178772},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.420365571975708},{"id":"https://openalex.org/keywords/spectral-resolution","display_name":"Spectral resolution","score":0.41428664326667786},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37079593539237976},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.2645733654499054},{"id":"https://openalex.org/keywords/spectral-line","display_name":"Spectral line","score":0.19808462262153625},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.17425185441970825},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.143023282289505}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8255324363708496},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.7665621638298035},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6155564785003662},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.6006175875663757},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.5927630662918091},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5645409226417542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4960375726222992},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4770978093147278},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4294772744178772},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.420365571975708},{"id":"https://openalex.org/C124967146","wikidata":"https://www.wikidata.org/wiki/Q3457898","display_name":"Spectral resolution","level":3,"score":0.41428664326667786},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37079593539237976},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.2645733654499054},{"id":"https://openalex.org/C4839761","wikidata":"https://www.wikidata.org/wiki/Q212111","display_name":"Spectral line","level":2,"score":0.19808462262153625},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.17425185441970825},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.143023282289505},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2020.3046321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3046321","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":[{"id":"https://metadata.un.org/sdg/9","score":0.41999998688697815,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2641283365","display_name":null,"funder_award_id":"2019A610098","funder_id":"https://openalex.org/F4320332587","funder_display_name":"Natural Science Foundation of Ningbo"},{"id":"https://openalex.org/G3409118948","display_name":"\u9886\u57df\u81ea\u9002\u5e94\u7684\u9ad8\u5149\u8c31\u9065\u611f\u667a\u80fd\u5206\u7c7b\u4e0e\u6ee8\u6d77\u6e7f\u5730\u5e94\u7528","funder_award_id":"LR19D010001","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G5568457102","display_name":null,"funder_award_id":"41971296","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5745640903","display_name":"\u9ad8\u5149\u8c31\u9065\u611f\u56fe\u50cf\u7684\u9c81\u68d2\u6838\u7a7a\u95f4\u8054\u5408\u7a00\u758f\u8868\u793a\u7814\u7a76","funder_award_id":"61871177","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G612811711","display_name":null,"funder_award_id":"LQ18D010001","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G6427993980","display_name":null,"funder_award_id":"U1609203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7534358263","display_name":null,"funder_award_id":"41801252","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7871462125","display_name":"\u57fa\u4e8e\u9ad8\u5149\u8c31\u591a\u7279\u5f81\u534f\u540c\u7a00\u758f\u8868\u8fbe\u7684\u6ee8\u6d77\u6e7f\u5730\u7cbe\u7ec6\u5206\u7c7b\u7814\u7a76","funder_award_id":"41671342","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8293725174","display_name":null,"funder_award_id":"41801256","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"},{"id":"https://openalex.org/F4320332587","display_name":"Natural Science Foundation of Ningbo","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1495168473","https://openalex.org/W1553305639","https://openalex.org/W1940108662","https://openalex.org/W1990231296","https://openalex.org/W1992229061","https://openalex.org/W1995686650","https://openalex.org/W2001800591","https://openalex.org/W2004661786","https://openalex.org/W2047302141","https://openalex.org/W2055910465","https://openalex.org/W2061295289","https://openalex.org/W2092575013","https://openalex.org/W2097915756","https://openalex.org/W2100329651","https://openalex.org/W2117146861","https://openalex.org/W2119077559","https://openalex.org/W2121219287","https://openalex.org/W2124073857","https://openalex.org/W2163677711","https://openalex.org/W2171108951","https://openalex.org/W2171211028","https://openalex.org/W2221899823","https://openalex.org/W2303172903","https://openalex.org/W2327364376","https://openalex.org/W2329177465","https://openalex.org/W2371660872","https://openalex.org/W2514340250","https://openalex.org/W2523686528","https://openalex.org/W2536760076","https://openalex.org/W2565258258","https://openalex.org/W2592312604","https://openalex.org/W2609880332","https://openalex.org/W2625894731","https://openalex.org/W2782223379","https://openalex.org/W2792111852","https://openalex.org/W2794048225","https://openalex.org/W2799929262","https://openalex.org/W2803825432","https://openalex.org/W2806865914","https://openalex.org/W2900702559","https://openalex.org/W2944395072","https://openalex.org/W2963442801","https://openalex.org/W3004968762","https://openalex.org/W3010650493","https://openalex.org/W3023221758","https://openalex.org/W3099843321","https://openalex.org/W3105997607","https://openalex.org/W6633088995"],"related_works":["https://openalex.org/W2018850895","https://openalex.org/W4205174160","https://openalex.org/W2024377932","https://openalex.org/W2084145074","https://openalex.org/W1978077614","https://openalex.org/W2889956472","https://openalex.org/W1982418987","https://openalex.org/W2799746630","https://openalex.org/W4390582117","https://openalex.org/W2020749638"],"abstract_inverted_index":{"The":[0,29,159],"nonoverlapped":[1,99,151,174],"spectrum":[2,30,40,60],"range":[3],"between":[4,106,148],"low":[5],"spatial":[6,13,83,215],"resolution":[7,14],"(LR)":[8],"hyperspectral":[9],"(HS)":[10],"and":[11,38,85,98,108,150,185,197,213,217,239],"high":[12,210],"(HR)":[15],"multispectral":[16],"(MS)":[17],"images":[18],"has":[19,205,230],"been":[20],"a":[21,69,111,133],"fundamental":[22],"but":[23],"challenging":[24],"problem":[25],"for":[26],"MS/HS":[27],"fusion.":[28],"of":[31,41,61,92,129,153,190],"HS":[32,54,93,107,157,169,176],"data":[33,43,183,188],"is":[34,44],"generally":[35,45],"400\u20132500":[36,62],"nm,":[37],"the":[39,51,58,76,89,103,126,137,144,154,165,173,202],"MS":[42,199],"400\u2013900":[46],"nm;":[47],"how":[48],"to":[49,74,102,124,142,164,171],"obtain":[50],"high-fidelity":[52],"HR":[53,168,175],"fused":[55,166],"image":[56],"within":[57],"whole":[59],"nm?":[63],"In":[64],"this":[65],"article,":[66],"we":[67],"proposed":[68,123,203],"band":[70],"divide-and-conquer":[71],"framework":[72],"(BDCF)":[73],"solve":[75],"problem,":[77],"by":[78,118],"comprehensively":[79],"considering":[80],"spectral":[81,90,104,211],"fidelity,":[82],"enhancement,":[84],"computational":[86,233],"efficiency.":[87],"First,":[88],"bands":[91,100,128,152,170],"were":[94],"divided":[95],"into":[96],"overlapped":[97,127,149,167],"according":[101],"response":[105],"MS.":[109],"Then,":[110,132],"novel":[112],"improved":[113],"component":[114],"substitution":[115],"(CS)-based":[116],"method":[117,135],"combing":[119],"neural":[120,138],"network":[121,139,161],"was":[122,140,162],"fuse":[125],"LR":[130,156,193],"HS.":[131],"mapping-based":[134],"with":[136,224],"presented":[141],"construct":[143],"complicated":[145],"nonlinear":[146],"relationship":[147],"original":[155],"data.":[158],"trained":[160],"mapped":[163],"estimate":[172],"bands.":[177],"Experimental":[178],"results":[179],"on":[180],"two":[181,186],"simulated":[182],"sets":[184,189],"realistic":[187],"Gaofen":[191],"(GF)-5":[192],"HS,":[194],"GF-1":[195],"MS,":[196],"Sentinel-2A":[198],"show":[200],"that":[201],"BDCF":[204,229],"superior":[206],"performance":[207],"in":[208],"both":[209],"fidelity":[212],"sharp":[214],"details,":[216],"it":[218],"obtained":[219],"competitive":[220],"fusion":[221,242],"behaviors":[222],"compared":[223],"other":[225],"state-of-the-art":[226],"methods.":[227,243],"Moreover,":[228],"relatively":[231],"higher":[232],"efficiency":[234],"than":[235],"optimal":[236],"solution-based":[237],"methods":[238],"deep":[240],"learning-based":[241]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":22},{"year":2021,"cited_by_count":7}],"updated_date":"2026-07-13T07:31:44.756512","created_date":"2025-10-10T00:00:00"}
