{"id":"https://openalex.org/W7083313211","doi":"https://doi.org/10.1109/tgrs.2025.3614444","title":"Full-Scale Regression Modeling of Spatial Details for Single-/Multiplatform Hypersharpening","display_name":"Full-Scale Regression Modeling of Spatial Details for Single-/Multiplatform Hypersharpening","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7083313211","doi":"https://doi.org/10.1109/tgrs.2025.3614444"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2025.3614444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3614444","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":null,"display_name":"Alberto Arienzo","orcid":"https://orcid.org/0000-0002-1584-4631"},"institutions":[{"id":"https://openalex.org/I4210115556","display_name":"National Research Council - Institute of Methodologies for Environmental Analysis","ror":"https://ror.org/024ye7w89","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210115556","https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alberto Arienzo","raw_affiliation_strings":["National Research Council-Institute of Methodologies for Environmental Analysis (CNR-IMAA), Tito Scalo, Italy"],"raw_orcid":"https://orcid.org/0000-0002-1584-4631","affiliations":[{"raw_affiliation_string":"National Research Council-Institute of Methodologies for Environmental Analysis (CNR-IMAA), Tito Scalo, Italy","institution_ids":["https://openalex.org/I4210115556"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Andrea Garzelli","orcid":"https://orcid.org/0000-0003-2332-780X"},"institutions":[{"id":"https://openalex.org/I102064193","display_name":"University of Siena","ror":"https://ror.org/01tevnk56","country_code":"IT","type":"education","lineage":["https://openalex.org/I102064193"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrea Garzelli","raw_affiliation_strings":["Department of Information Engineering and Mathematics, University of Siena, Siena, Italy"],"raw_orcid":"https://orcid.org/0000-0003-2332-780X","affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Mathematics, University of Siena, Siena, Italy","institution_ids":["https://openalex.org/I102064193"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Luciano Alparone","orcid":"https://orcid.org/0000-0002-8984-938X"},"institutions":[{"id":"https://openalex.org/I45084792","display_name":"University of Florence","ror":"https://ror.org/04jr1s763","country_code":"IT","type":"education","lineage":["https://openalex.org/I45084792"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luciano Alparone","raw_affiliation_strings":["Department of Information Engineering, University of Florence, Florence, Italy"],"raw_orcid":"https://orcid.org/0000-0002-8984-938X","affiliations":[{"raw_affiliation_string":"Department of Information Engineering, University of Florence, Florence, Italy","institution_ids":["https://openalex.org/I45084792"]}]},{"author_position":"last","author":{"id":null,"display_name":"Gemine Vivone","orcid":"https://orcid.org/0000-0001-9542-0638"},"institutions":[{"id":"https://openalex.org/I4210115556","display_name":"National Research Council - Institute of Methodologies for Environmental Analysis","ror":"https://ror.org/024ye7w89","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210115556","https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Gemine Vivone","raw_affiliation_strings":["National Research Council-Institute of Methodologies for Environmental Analysis (CNR-IMAA), Tito Scalo, Italy"],"raw_orcid":"https://orcid.org/0000-0001-9542-0638","affiliations":[{"raw_affiliation_string":"National Research Council-Institute of Methodologies for Environmental Analysis (CNR-IMAA), Tito Scalo, Italy","institution_ids":["https://openalex.org/I4210115556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.4401,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91767532,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.7017999887466431,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.7017999887466431,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T13067","display_name":"Geological Modeling and Analysis","score":0.02759999968111515,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14311","display_name":"Electrical and Electromagnetic Research","score":0.016100000590085983,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sharpening","display_name":"Sharpening","score":0.8603000044822693},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5799999833106995},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.5723000168800354},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5691999793052673},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.47609999775886536},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4674000144004822},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4569999873638153},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4065999984741211},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37959998846054077}],"concepts":[{"id":"https://openalex.org/C2781137444","wikidata":"https://www.wikidata.org/wiki/Q237105","display_name":"Sharpening","level":2,"score":0.8603000044822693},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.659500002861023},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5799999833106995},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.5723000168800354},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5691999793052673},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.47609999775886536},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4569999873638153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4487999975681305},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4244000017642975},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4065999984741211},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37959998846054077},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.37470000982284546},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.35600000619888306},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.3517000079154968},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.3407000005245209},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33079999685287476},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.3257000148296356},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3131999969482422},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.30660000443458557},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.29089999198913574},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C100921725","wikidata":"https://www.wikidata.org/wiki/Q1650811","display_name":"Spatial frequency","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25429999828338623}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tgrs.2025.3614444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3614444","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:flore.unifi.it:2158/1437698","is_oa":false,"landing_page_url":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11179947&utm_source=scopus&getft_integrator=scopus&tag=1","pdf_url":null,"source":{"id":"https://openalex.org/S4306402033","display_name":"Florence Research (University of Florence)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45084792","host_organization_name":"University of Florence","host_organization_lineage":["https://openalex.org/I45084792"],"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":"info:eu-repo/semantics/article"},{"id":"pmh:oai:usiena-air.unisi.it:11365/1301035","is_oa":false,"landing_page_url":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11179947","pdf_url":null,"source":{"id":"https://openalex.org/S4377196319","display_name":"Use Siena air (University of Siena)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I102064193","host_organization_name":"University of Siena","host_organization_lineage":["https://openalex.org/I102064193"],"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":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Whenever":[0],"the":[1,7,43,54,62,84,94,143,151,200,203,208],"sharpening":[2,55],"band":[3,72,86],"is":[4,25,97],"not":[5],"unique,":[6],"hypersharpening":[8,108],"paradigm":[9],"extends":[10],"traditional":[11],"pansharpening":[12],"to":[13,41,87,99,146],"anym-to-nfusion":[14],"task,":[15],"by":[16,30,199],"integrating":[17],"spatial":[18,114,153,219],"information":[19],"from":[20,156],"multiple":[21],"sources.":[22],"Them-to-nfusion":[23],"task":[24],"recast":[26],"into":[27],"multiple1-to-npansharpening":[28],"problems":[29],"appropriately":[31],"selecting":[32],"or":[33],"synthesizing":[34],"a":[35,58,77,106,132],"set":[36,44],"of":[37,45,53,61,69,93,207],"high-resolution":[38],"(HR)":[39],"bands":[40,56,96],"sharpen":[42],"low-resolution":[46],"(LR)":[47],"bands.":[48,65],"The":[49,66],"synthesis":[50],"generates":[51],"each":[52,70,100],"as":[57,175],"linear":[59,79],"combination":[60,92],"available":[63],"HR":[64,95],"spectral":[67,221],"coefficients":[68],"synthetic":[71],"can":[73],"be":[74,88,147],"estimated":[75],"using":[76],"multivariate":[78],"regression":[80],"(MLR)":[81],"that":[82,110,141],"matches":[83],"LR":[85,101],"sharpened.":[89],"A":[90],"different":[91],"assimilated":[98],"band.":[102],"Here,":[103],"we":[104,136,160],"propose":[105],"novel":[107],"instance":[109],"directly":[111,148],"combines":[112],"high-pass":[113],"details,":[115],"rather":[116],"than":[117],"lowpass":[118],"image":[119],"components.":[120],"In":[121],"general,":[122],"fusion":[123,144,215],"methods":[124],"optimize":[125],"their":[126],"parameters":[127,145],"at":[128,150,189],"reduced":[129,190],"scale,":[130],"assuming":[131],"scale-invariance":[133],"property.":[134],"Instead,":[135],"introduce":[137],"an":[138,157,162],"estimation":[139],"strategy":[140],"allows":[142],"retrieved":[149],"full":[152,192],"scale.":[154],"Starting":[155],"iterative":[158],"process,":[159],"derive":[161],"asymptotic":[163],"closed-form":[164],"solution":[165,210],"and":[166,181,185,191,205,213,223],"establish":[167],"its":[168],"convergence":[169],"conditions.":[170],"Three":[171],"case":[172],"studies":[173],"involving":[174],"many":[176],"real":[177],"datasets\u2014Sentinel-2,":[178],"Environmental":[179],"Mapping":[180],"Analysis":[182],"Program":[183],"(EnMAP),":[184],"WorldView-3\u2014demonstrate":[186],"performance":[187],"improvements":[188],"resolutions,":[193,220],"obtained":[194],"without":[195],"any":[196],"parametric":[197],"optimization":[198],"user,":[201],"confirming":[202],"effectiveness":[204],"versatility":[206],"proposed":[209],"in":[211],"single-":[212],"multiplatform":[214],"scenarios":[216],"featuring":[217],"diverse":[218],"bands,":[222],"resolution":[224],"ratios.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}