{"id":"https://openalex.org/W4402259218","doi":"https://doi.org/10.1109/igarss53475.2024.10642880","title":"Unsupervised Blind Hyperspectral Super-Resolution for Unregistered Images","display_name":"Unsupervised Blind Hyperspectral Super-Resolution for Unregistered Images","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402259218","doi":"https://doi.org/10.1109/igarss53475.2024.10642880"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10642880","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10642880","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":"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/A5057875898","display_name":"Baiyang Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baiyang Hu","raw_affiliation_strings":["Beijing Institute of Technology,Key Laboratory of Photoelectronic Imaging Technology and System"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology,Key Laboratory of Photoelectronic Imaging Technology and System","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027895444","display_name":"Xiaodian Zhang","orcid":"https://orcid.org/0000-0001-9719-2069"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodian Zhang","raw_affiliation_strings":["Beijing Institute of Technology,Key Laboratory of Photoelectronic Imaging Technology and System"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology,Key Laboratory of Photoelectronic Imaging Technology and System","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039422903","display_name":"Kun Gao","orcid":"https://orcid.org/0000-0002-2394-2653"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Gao","raw_affiliation_strings":["Beijing Institute of Technology,Key Laboratory of Photoelectronic Imaging Technology and System"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology,Key Laboratory of Photoelectronic Imaging Technology and System","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.5637,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.70919522,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"9349","last_page":"9352"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9986000061035156,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8770325183868408},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6470582485198975},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6306682825088501},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5948811173439026},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.48013827204704285},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42932796478271484},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.41596999764442444},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.40000367164611816},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.2138487994670868}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8770325183868408},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6470582485198975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6306682825088501},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5948811173439026},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.48013827204704285},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42932796478271484},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.41596999764442444},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.40000367164611816},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2138487994670868}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10642880","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10642880","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":0.49000000953674316,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1495168473","https://openalex.org/W1990231296","https://openalex.org/W2001800591","https://openalex.org/W2625894731","https://openalex.org/W2804744787","https://openalex.org/W2941707854","https://openalex.org/W2962770389","https://openalex.org/W2963442801","https://openalex.org/W3010675358","https://openalex.org/W3048794210","https://openalex.org/W3097353710","https://openalex.org/W3098388691","https://openalex.org/W4294663621","https://openalex.org/W4383813293","https://openalex.org/W4385453538"],"related_works":["https://openalex.org/W2385371209","https://openalex.org/W4250051149","https://openalex.org/W2083270190","https://openalex.org/W1991437568","https://openalex.org/W2317401237","https://openalex.org/W1990800631","https://openalex.org/W2167120702","https://openalex.org/W2579567122","https://openalex.org/W2362774332","https://openalex.org/W4249245269"],"abstract_inverted_index":{"Hyperspectral":[0],"images":[1,13],"super-resolution":[2],"(HSI-SR)":[3],"aims":[4],"to":[5,37,81,96,142],"fuse":[6],"low-resolution":[7],"HSI":[8,77],"(LR-HSIs)":[9],"and":[10,26,58,85,106],"high-resolution":[11,16],"multispectral":[12],"(HR-MSIs)":[14],"for":[15,55],"HSIs":[17,57],"(HR-HSIs).":[18],"Most":[19],"existing":[20,143],"methods":[21],"require":[22],"registered":[23,98],"image":[24],"pairs":[25],"prior":[27],"knowledge":[28],"of":[29,62,111,119,140],"spectral":[30],"response":[31],"functions":[32],"(SRFs),":[33],"which":[34],"requires":[35],"effort":[36],"realize":[38],"in":[39],"practical":[40],"applications.":[41],"To":[42],"overcome":[43],"this":[44,46],"limitation,":[45],"paper":[47],"proposes":[48],"an":[49],"unsupervised":[50],"blind":[51],"HSI-SR":[52],"method":[53],"(UBHSI-SR)":[54],"unregistered":[56],"MSIs.":[59],"UBHSI-SR":[60,141],"consists":[61],"two":[63],"unmixing":[64,78],"branches,":[65],"each":[66],"having":[67],"its":[68],"own":[69],"encoder":[70],"while":[71],"sharing":[72],"the":[73,76,91,97,109,112,116,121,125,137],"decoder.":[74],"First,":[75],"branch":[79],"learns":[80,86],"predict":[82],"abundance":[83,101,117],"maps":[84,118],"precise":[87],"endmember":[88],"spectra.":[89],"Then,":[90],"learnable":[92],"SRF":[93],"transfers":[94],"LR-HSIs":[95,105],"LR-MSIs.":[99],"The":[100],"similarity":[102],"constraint":[103],"between":[104],"LR-MSIs":[107],"guides":[108],"learning":[110],"MSI":[113],"encoder.":[114],"With":[115],"HR-MSI,":[120],"shared":[122],"decoder":[123],"predicts":[124],"HR-HSIs":[126],"as":[127],"final":[128],"results.":[129],"Experiments":[130],"on":[131],"three":[132],"remote":[133],"sensing":[134],"datasets":[135],"validate":[136],"superior":[138],"performance":[139],"fusion":[144],"methods.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
