{"id":"https://openalex.org/W4402259997","doi":"https://doi.org/10.1109/igarss53475.2024.10640666","title":"Enhancing Hyperspectral Pansharpening with Local-Tensor-Nuclear-Norm Regularization","display_name":"Enhancing Hyperspectral Pansharpening with Local-Tensor-Nuclear-Norm Regularization","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402259997","doi":"https://doi.org/10.1109/igarss53475.2024.10640666"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10640666","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10640666","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5113368510","display_name":"Keiya Okazaki","orcid":null},"institutions":[{"id":"https://openalex.org/I17056963","display_name":"The University of Kitakyushu","ror":"https://ror.org/03mfefw72","country_code":"JP","type":"education","lineage":["https://openalex.org/I17056963"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keiya Okazaki","raw_affiliation_strings":["The University of Kitakyushu,Faculty of Environmental Engineering,Fukuoka,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Kitakyushu,Faculty of Environmental Engineering,Fukuoka,Japan","institution_ids":["https://openalex.org/I17056963"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107013015","display_name":"Atsuya Emoto","orcid":null},"institutions":[{"id":"https://openalex.org/I17056963","display_name":"The University of Kitakyushu","ror":"https://ror.org/03mfefw72","country_code":"JP","type":"education","lineage":["https://openalex.org/I17056963"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsuya Emoto","raw_affiliation_strings":["The University of Kitakyushu,Faculty of Environmental Engineering,Fukuoka,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Kitakyushu,Faculty of Environmental Engineering,Fukuoka,Japan","institution_ids":["https://openalex.org/I17056963"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044657759","display_name":"Ryo Matsuoka","orcid":"https://orcid.org/0000-0002-2317-5845"},"institutions":[{"id":"https://openalex.org/I17056963","display_name":"The University of Kitakyushu","ror":"https://ror.org/03mfefw72","country_code":"JP","type":"education","lineage":["https://openalex.org/I17056963"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryo Matsuoka","raw_affiliation_strings":["The University of Kitakyushu,Faculty of Environmental Engineering,Fukuoka,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Kitakyushu,Faculty of Environmental Engineering,Fukuoka,Japan","institution_ids":["https://openalex.org/I17056963"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I17056963"],"apc_list":null,"apc_paid":null,"fwci":0.7967,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.71110487,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"9285","last_page":"9289"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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":0.8627289533615112},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5312590003013611},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.46961575746536255},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.43957749009132385},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.4211253821849823},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.402437299489975},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3948112726211548},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39333999156951904},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32002386450767517},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.20441976189613342},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.1549580693244934},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.08558166027069092},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.08542317152023315}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8627289533615112},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5312590003013611},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.46961575746536255},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.43957749009132385},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.4211253821849823},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.402437299489975},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3948112726211548},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39333999156951904},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32002386450767517},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.20441976189613342},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.1549580693244934},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.08558166027069092},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.08542317152023315},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10640666","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10640666","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1799163428","https://openalex.org/W2010319424","https://openalex.org/W2021046129","https://openalex.org/W2029316659","https://openalex.org/W2045079045","https://openalex.org/W2078855750","https://openalex.org/W2087263574","https://openalex.org/W2097915756","https://openalex.org/W2133665775","https://openalex.org/W2142377456","https://openalex.org/W2142552707","https://openalex.org/W2766846559","https://openalex.org/W2782517596","https://openalex.org/W2791928749","https://openalex.org/W2794203054","https://openalex.org/W2802729498","https://openalex.org/W2942454403","https://openalex.org/W2948669395","https://openalex.org/W2953478519","https://openalex.org/W2963442801","https://openalex.org/W2964214749","https://openalex.org/W3075397214","https://openalex.org/W3102912004","https://openalex.org/W3132916202","https://openalex.org/W3133821040","https://openalex.org/W3181737610","https://openalex.org/W3209566058","https://openalex.org/W3213530674","https://openalex.org/W4226507018","https://openalex.org/W4292363360","https://openalex.org/W4387829230","https://openalex.org/W6602248423"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2969683494","https://openalex.org/W2953204310","https://openalex.org/W2030927653","https://openalex.org/W2062063412","https://openalex.org/W3155724094"],"abstract_inverted_index":{"In":[0,47],"this":[1],"paper,":[2],"we":[3,51,76],"propose":[4],"a":[5],"robust":[6],"hyperspectral":[7],"(HS)":[8],"pansharpening":[9],"method":[10],"that":[11],"combines":[12],"the":[13,21,40,43,48,56,67,92,96],"total":[14],"nuclear":[15,24],"norms":[16,25],"of":[17,42,69,98],"gradients":[18],"(TNNG)":[19],"and":[20,80,87,89],"local":[22,61],"tensor":[23],"(LTNN)":[26],"for":[27],"regularization.":[28],"While":[29],"conventional":[30,79],"TNNG":[31],"regularization":[32,54],"can":[33],"reduce":[34,39],"noise,":[35],"it":[36],"tends":[37],"to":[38,59,83,94],"rank":[41,72],"spectral":[44,62,71],"domain":[45,58],"excessively.":[46],"proposed":[49,81],"method,":[50],"incorporate":[52],"LTNN":[53],"in":[55],"spatial":[57],"promote":[60],"low":[63],"rankness,":[64],"thereby":[65],"mitigating":[66],"problem":[68],"excessive":[70],"reduction.":[73],"Through":[74],"experiments,":[75],"apply":[77],"both":[78],"methods":[82],"various":[84],"HS":[85],"images":[86],"quantitatively":[88],"qualitatively":[90],"compare":[91],"results":[93],"demonstrate":[95],"effectiveness":[97],"our":[99],"method.":[100]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
