{"id":"https://openalex.org/W4387010858","doi":"https://doi.org/10.1109/tgrs.2023.3319069","title":"Multiple Deep Proximal Learning for Hyperspectral-Multispectral Image Fusion","display_name":"Multiple Deep Proximal Learning for Hyperspectral-Multispectral Image Fusion","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4387010858","doi":"https://doi.org/10.1109/tgrs.2023.3319069"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3319069","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3319069","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/A5024727500","display_name":"Jingxiang Yang","orcid":"https://orcid.org/0000-0002-1234-0614"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]},{"id":"https://openalex.org/I4210140549","display_name":"Skyworth (China)","ror":"https://ror.org/03wb8cw02","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210140549"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jingxiang Yang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","Nanjing Skyworth Institute of Information Technology Co., Ltd, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-1234-0614","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"Nanjing Skyworth Institute of Information Technology Co., Ltd, Nanjing, China","institution_ids":["https://openalex.org/I4210140549"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009777586","display_name":"Tian Lin","orcid":"https://orcid.org/0009-0006-7022-6218"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Lin","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0006-7022-6218","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101531064","display_name":"Xiaoyang Chen","orcid":"https://orcid.org/0000-0002-4291-2900"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]},{"id":"https://openalex.org/I4210151935","display_name":"Dahua Technology (China)","ror":"https://ror.org/04k9ktn61","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210151935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyang Chen","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","Zhejiang Dahua Technology Co., Ltd, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4291-2900","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"Zhejiang Dahua Technology Co., Ltd, Hangzhou, China","institution_ids":["https://openalex.org/I4210151935"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020302879","display_name":"Liang Xiao","orcid":"https://orcid.org/0000-0003-0178-9384"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Xiao","raw_affiliation_strings":["School of Computer Science and Engineering and the Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, China","School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-0178-9384","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering and the Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024727500"],"corresponding_institution_ids":["https://openalex.org/I36399199","https://openalex.org/I4210140549"],"apc_list":null,"apc_paid":null,"fwci":1.6581,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.86021268,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"14"},"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":0.9995999932289124,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9969000220298767,"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":0.7469860315322876},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7319114208221436},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7150963544845581},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.6192455291748047},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6072540283203125},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5518379211425781},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4555285573005676},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.44542941451072693},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35084134340286255},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.28845280408859253}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7469860315322876},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7319114208221436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7150963544845581},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.6192455291748047},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6072540283203125},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5518379211425781},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4555285573005676},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.44542941451072693},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35084134340286255},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28845280408859253},{"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":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3319069","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3319069","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/G2211911332","display_name":null,"funder_award_id":"30920021134","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G292805373","display_name":null,"funder_award_id":"62001226","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5667856390","display_name":null,"funder_award_id":"BK20200465","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G6529097563","display_name":null,"funder_award_id":"JSGP202204","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7865873667","display_name":"\u57fa\u4e8e\u5149\u6805\u9635\u5217\u548c\u6df1\u5ea6\u5b66\u4e60\u7684\u504f\u632f\u5149\u8c31\u6210\u50cf\u7406\u8bba\u7814\u7a76","funder_award_id":"61771391","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8432856719","display_name":null,"funder_award_id":"61871226","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/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1940108662","https://openalex.org/W1990231296","https://openalex.org/W2012946078","https://openalex.org/W2021046129","https://openalex.org/W2072445211","https://openalex.org/W2097259623","https://openalex.org/W2221899823","https://openalex.org/W2508457857","https://openalex.org/W2520430674","https://openalex.org/W2603834682","https://openalex.org/W2614326984","https://openalex.org/W2625894731","https://openalex.org/W2745541172","https://openalex.org/W2784344583","https://openalex.org/W2803825432","https://openalex.org/W2804744787","https://openalex.org/W2910457605","https://openalex.org/W2945202593","https://openalex.org/W2949128855","https://openalex.org/W2954661277","https://openalex.org/W2964140612","https://openalex.org/W2983315964","https://openalex.org/W2989355516","https://openalex.org/W2990162903","https://openalex.org/W2991616716","https://openalex.org/W2997011911","https://openalex.org/W3016410830","https://openalex.org/W3027521166","https://openalex.org/W3041293645","https://openalex.org/W3048794210","https://openalex.org/W3097353710","https://openalex.org/W3099239430","https://openalex.org/W3099843321","https://openalex.org/W3102025760","https://openalex.org/W3102912004","https://openalex.org/W3132115664","https://openalex.org/W3160949528","https://openalex.org/W3167568784","https://openalex.org/W3168080945","https://openalex.org/W3186573928","https://openalex.org/W3196386002","https://openalex.org/W3196711624","https://openalex.org/W3199351457","https://openalex.org/W3207918547","https://openalex.org/W3212854333","https://openalex.org/W3216963209","https://openalex.org/W4210330613","https://openalex.org/W4221166810","https://openalex.org/W4225672218","https://openalex.org/W4293811844","https://openalex.org/W4312812783","https://openalex.org/W4312999834","https://openalex.org/W4315778328","https://openalex.org/W4317528595","https://openalex.org/W4367834188","https://openalex.org/W4378421719","https://openalex.org/W4378804827","https://openalex.org/W4386065834","https://openalex.org/W6799182923"],"related_works":["https://openalex.org/W2022304901","https://openalex.org/W2018850895","https://openalex.org/W2988577871","https://openalex.org/W1987483041","https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3152170969","https://openalex.org/W2139242969","https://openalex.org/W2379054866","https://openalex.org/W2549658594"],"abstract_inverted_index":{"Fusing":[0],"low":[1],"resolution":[2,10,19],"(LR)":[3],"hyperspectral":[4],"image":[5,13],"(HSI)":[6],"with":[7,45,49,61,101,206],"a":[8,71,96,153,186],"high":[9],"(HR)":[11],"multispectral":[12],"(MSI)":[14],"could":[15],"enhance":[16],"the":[17,50,81,103,121,150,161,178,193,201,217],"spatial":[18],"and":[20,85,105,127,137,167,195],"quality":[21],"of":[22,42],"HSI.":[23],"Current":[24],"deep":[25,73,116,145,162,179],"learning":[26,75],"(DL)":[27],"HSI-MSI":[28,79],"fusion":[29,99,122,208],"networks":[30],"have":[31],"achieved":[32],"encouraging":[33],"results,":[34],"but":[35],"their":[36],"performance":[37],"relies":[38],"on":[39,59],"large":[40],"number":[41],"training":[43],"images":[44],"known":[46],"degradations":[47,63,84,104,166],"consistent":[48],"testing":[51],"data.":[52],"The":[53,131],"trained":[54],"DL":[55,154],"model":[56,100,123],"may":[57],"fail":[58],"data":[60],"unseen":[62,218],"during":[64],"inference.":[65],"In":[66],"this":[67],"study,":[68],"we":[69,119,156],"propose":[70,95],"multiple":[72,115],"proximal":[74,146,163,180],"network":[76],"(MDPro-Net)":[77],"for":[78,165,182],"fusion,":[80],"unknown":[82,132],"spatial-spectral":[83],"latent":[86,183],"HR":[87,106,138,168,184],"HSI":[88,107,139,169],"can":[89],"be":[90],"adaptively":[91],"inferred.":[92],"We":[93],"first":[94],"joint":[97],"variational":[98],"both":[102],"as":[108],"to-be-solved":[109],"variables,":[110],"which":[111,160],"are":[112,140,170],"regularized":[113],"by":[114,143],"priors.":[117],"Then":[118],"optimize":[120],"using":[124],"quadratic":[125],"splitting":[126],"alternative":[128],"optimization":[129],"strategy.":[130],"blurring":[133],"kernel,":[134],"spectral":[135],"degradation,":[136],"explicitly":[141],"solved":[142],"three":[144],"operators.":[147],"Through":[148],"unrolling":[149],"solutions":[151],"into":[152],"network,":[155],"build":[157],"MDPro-Net,":[158],"in":[159,172,177,210,215],"operators":[164],"learned":[171],"an":[173],"end-to-end":[174],"manner.":[175],"Furthermore,":[176],"operator":[181],"HSI,":[185],"multi-scale":[187],"transformer":[188],"is":[189,204,213],"designed":[190],"to":[191],"exploit":[192],"local":[194],"non-local":[196],"dependencies.":[197],"Experiments":[198],"demonstrate":[199],"that":[200],"proposed":[202],"MDPro-Net":[203],"competitive":[205],"state-of-the-art":[207],"methods,":[209],"particular,":[211],"it":[212],"robust":[214],"inferring":[216],"degradations.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6}],"updated_date":"2026-06-06T09:05:17.133730","created_date":"2025-10-10T00:00:00"}
