{"id":"https://openalex.org/W2890244317","doi":"https://doi.org/10.1109/icassp.2018.8462525","title":"Hyperspectral Super-Resolution Via Coupled Tensor Factorization: Identifiability and Algorithms","display_name":"Hyperspectral Super-Resolution Via Coupled Tensor Factorization: Identifiability and Algorithms","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2890244317","doi":"https://doi.org/10.1109/icassp.2018.8462525","mag":"2890244317"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2018.8462525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8462525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-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/A5034936665","display_name":"Charilaos I. Kanatsoulis","orcid":"https://orcid.org/0000-0002-0952-1561"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charilaos I. Kanatsoulis","raw_affiliation_strings":["Department of ECE, University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of ECE, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015075381","display_name":"Xiao Fu","orcid":"https://orcid.org/0000-0003-4847-9586"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiao Fu","raw_affiliation_strings":["School of EECS, Oregon State University, Corvallis, OR, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of EECS, Oregon State University, Corvallis, OR, USA","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050186120","display_name":"Nicholas D. Sidiropoulos","orcid":"https://orcid.org/0000-0002-3385-7911"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicholas D. Sidiropoulos","raw_affiliation_strings":["Department of ECE, University of Virginia, Charlottesville, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of ECE, University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016986549","display_name":"Wing\u2010Kin Ma","orcid":"https://orcid.org/0000-0001-7314-3537"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wing-Kin Ma","raw_affiliation_strings":["Departrnem of EE, The Chinese University of Hong Kong, Shatin, NT, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departrnem of EE, The Chinese University of Hong Kong, Shatin, NT, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1377,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.9285633,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3191","last_page":"3195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.875229001045227},{"id":"https://openalex.org/keywords/identifiability","display_name":"Identifiability","score":0.7117540240287781},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6611362099647522},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.6133275032043457},{"id":"https://openalex.org/keywords/panchromatic-film","display_name":"Panchromatic film","score":0.5928367376327515},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5542383790016174},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5377585887908936},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.4767911434173584},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46527644991874695},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4623258411884308},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.4545733630657196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3869306147098541},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3471931219100952},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25246989727020264},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20297804474830627}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.875229001045227},{"id":"https://openalex.org/C122770356","wikidata":"https://www.wikidata.org/wiki/Q1656753","display_name":"Identifiability","level":2,"score":0.7117540240287781},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6611362099647522},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.6133275032043457},{"id":"https://openalex.org/C107445234","wikidata":"https://www.wikidata.org/wiki/Q280995","display_name":"Panchromatic film","level":3,"score":0.5928367376327515},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5542383790016174},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5377585887908936},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.4767911434173584},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46527644991874695},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4623258411884308},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.4545733630657196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3869306147098541},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3471931219100952},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25246989727020264},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20297804474830627},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2018.8462525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8462525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W846821018","https://openalex.org/W1940108662","https://openalex.org/W1970195563","https://openalex.org/W1971335521","https://openalex.org/W1990231296","https://openalex.org/W2021046129","https://openalex.org/W2024165284","https://openalex.org/W2063790512","https://openalex.org/W2097259623","https://openalex.org/W2106005123","https://openalex.org/W2137707174","https://openalex.org/W2171845746","https://openalex.org/W2194818953","https://openalex.org/W2221899823","https://openalex.org/W2323104748","https://openalex.org/W2469230926","https://openalex.org/W2513096609","https://openalex.org/W2528170672","https://openalex.org/W2752365628","https://openalex.org/W2963442801","https://openalex.org/W3099843321","https://openalex.org/W3102912004","https://openalex.org/W3104960002","https://openalex.org/W6642991451","https://openalex.org/W6685078114"],"related_works":["https://openalex.org/W2158394102","https://openalex.org/W1930929277","https://openalex.org/W2361746014","https://openalex.org/W1502637513","https://openalex.org/W2124952510","https://openalex.org/W2375311607","https://openalex.org/W2022261651","https://openalex.org/W4285005667","https://openalex.org/W2950729865","https://openalex.org/W2565514930"],"abstract_inverted_index":{"This":[0,44],"work":[1,147],"focuses":[2],"on":[3,34],"the":[4,39,62,88,92,96,135,138,151,173,176],"problem":[5],"of":[6,38,137,175],"fusing":[7],"a":[8,13,19,119],"hyperspectral":[9],"image":[10,15,21,64,94,140],"(HSI)":[11],"and":[12,26,42,98],"multispectral":[14],"(MSI)":[16],"to":[17,48,95,159,171],"produce":[18],"super-resolution":[20,63,93,139],"that":[22,87,125],"admits":[23],"high":[24],"spatial":[25,152],"spectral":[27],"resolutions.":[28],"Existing":[29],"algorithms":[30,85],"are":[31,100,169],"mostly":[32],"based":[33],"joint":[35],"low-rank":[36],"factorization":[37],"ma-tricized":[40],"HSI":[41,97],"MSI.":[43],"framework":[45],"is":[46,57,65,109],"effective":[47],"some":[49],"extent,":[50],"but":[51],"several":[52],"challenges":[53],"remain.":[54],"First,":[55],"it":[56],"unclear":[58],"whether":[59],"or":[60,102],"not":[61],"identifiable":[66],"in":[67,79,112,162],"theory":[68],"under":[69,141],"this":[70,115],"framework,":[71],"while":[72],"identifiability":[73,136],"usually":[74],"plays":[75],"an":[76],"essential":[77],"role":[78],"such":[80],"estimation":[81],"problems.":[82],"Second,":[83],"most":[84],"assume":[86],"degradation":[89,153],"operators":[90],"from":[91],"MSI":[99],"known":[101],"can":[103,126,146],"be":[104,157],"easily":[105],"estimated":[106],"-":[107],"which":[108,155],"hardly":[110],"true":[111],"practice.":[113,163],"In":[114],"work,":[116],"we":[117],"propose":[118],"novel":[120],"coupled":[121],"tensor":[122],"decomposition":[123],"method":[124,145],"effectively":[127],"circumvent":[128],"these":[129],"issues.":[130],"The":[131,144],"proposed":[132,177],"approach":[133],"guarantees":[134],"realistic":[142],"conditions.":[143],"even":[148],"without":[149],"knowing":[150],"operator,":[154],"could":[156],"hard":[158],"accurately":[160],"estimate":[161],"Simulations":[164],"using":[165],"AVIRIS":[166],"Cuprite":[167],"data":[168],"employed":[170],"demonstrate":[172],"effectiveness":[174],"approach.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}