{"id":"https://openalex.org/W4403780861","doi":"https://doi.org/10.1145/3664647.3681687","title":"SCPSN: Spectral Clustering-based Pyramid Super-resolution Network for Hyperspectral Images","display_name":"SCPSN: Spectral Clustering-based Pyramid Super-resolution Network for Hyperspectral Images","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403780861","doi":"https://doi.org/10.1145/3664647.3681687"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3681687","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","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/A5103660861","display_name":"Yong Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yong Yang","raw_affiliation_strings":["School of Computer Science and Technology, Tiangong University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-9467-0942","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110851120","display_name":"Angela Zhao","orcid":"https://orcid.org/0009-0000-5508-2603"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aoqi Zhao","raw_affiliation_strings":["School of Computer Science and Technology, Tiangong University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0000-5508-2603","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007731912","display_name":"Shuying Huang","orcid":"https://orcid.org/0000-0002-7845-2221"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuying Huang","raw_affiliation_strings":["School of Software, Tiangong University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-7845-2221","affiliations":[{"raw_affiliation_string":"School of Software, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086151419","display_name":"Xiaozheng Wang","orcid":"https://orcid.org/0000-0001-7841-3073"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaozheng Wang","raw_affiliation_strings":["School of Control Science and Engineering, Tiangong University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-7841-3073","affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115604087","display_name":"Yajing Fan","orcid":"https://orcid.org/0009-0008-4470-7282"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yajing Fan","raw_affiliation_strings":["School of Electronics and Information Engineering, Tiangong University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0008-4470-7282","affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103660861"],"corresponding_institution_ids":["https://openalex.org/I198091727"],"apc_list":null,"apc_paid":null,"fwci":0.6152,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.7349383,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2662","last_page":"2670"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994000196456909,"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":0.9986000061035156,"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":0.9180657863616943},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.693733811378479},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6329953670501709},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6306837797164917},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6130786538124084},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5074672102928162},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.47411778569221497},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.4418138861656189},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4331076443195343},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.4285467863082886},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40825027227401733},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.29642945528030396},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14919829368591309}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9180657863616943},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.693733811378479},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6329953670501709},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6306837797164917},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6130786538124084},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5074672102928162},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.47411778569221497},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.4418138861656189},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4331076443195343},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.4285467863082886},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40825027227401733},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.29642945528030396},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14919829368591309},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3681687","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2119681632","https://openalex.org/W2129471536","https://openalex.org/W2767522909","https://openalex.org/W2793775504","https://openalex.org/W2884727136","https://openalex.org/W2898062170","https://openalex.org/W2908833896","https://openalex.org/W2963091558","https://openalex.org/W2964164961","https://openalex.org/W2998841120","https://openalex.org/W3025440211","https://openalex.org/W3043719198","https://openalex.org/W3099608030","https://openalex.org/W3102745911","https://openalex.org/W3104467360","https://openalex.org/W3123265576","https://openalex.org/W3124196789","https://openalex.org/W3128204528","https://openalex.org/W3138516171","https://openalex.org/W3171125843","https://openalex.org/W3184720854","https://openalex.org/W3187800423","https://openalex.org/W3207918547","https://openalex.org/W4214947578","https://openalex.org/W4226469049","https://openalex.org/W4285202680","https://openalex.org/W4285270909","https://openalex.org/W4321483944","https://openalex.org/W4366148227","https://openalex.org/W4366668484","https://openalex.org/W4386766980","https://openalex.org/W4390873790"],"related_works":["https://openalex.org/W2317401237","https://openalex.org/W1990800631","https://openalex.org/W2167120702","https://openalex.org/W2579567122","https://openalex.org/W2362774332","https://openalex.org/W4249245269","https://openalex.org/W2765548132","https://openalex.org/W2025681766","https://openalex.org/W2542402767","https://openalex.org/W3023086044"],"abstract_inverted_index":{"Single":[0],"hyperspectral":[1,9,17],"image":[2,10,18,38,93],"super-resolution":[3,81,98],"aims":[4],"to":[5,28,84,120,143,188,202,228,232,247,276],"reconstruct":[6,86,203],"a":[7,77,96,138,180,195],"high-resolution":[8],"(HRHSI)":[11],"from":[12],"an":[13,64],"observed":[14],"low":[15],"resolution":[16],"(LRHSI).":[19],"Most":[20],"current":[21],"methods":[22,255],"combine":[23],"CNN":[24],"and":[25,56,63,113,149,162,217,226,261,281],"Transformer":[26],"structures":[27],"directly":[29],"extract":[30],"features":[31,176,191,205],"of":[32,47,102,124,146,151,158,166,175,192,206,243,249,258],"all":[33,207],"channels":[34,148,208,223,231],"in":[35,50,54,59,66,136,209,256],"LRHSI":[36,210],"for":[37,128],"reconstruction,":[39],"but":[40],"they":[41],"do":[42],"not":[43,269],"consider":[44],"the":[45,60,122,129,156,163,167,172,178,190,204,221,229,234,241],"interference":[46,157],"redundant":[48,159],"information":[49,161],"adjacent":[51,133],"bands,":[52],"resulting":[53],"spectral":[55,78,103,134,147,160],"spatial":[57],"distortions":[58],"reconstruction":[61,94,123],"results":[62],"increase":[65],"model":[67,267],"computational":[68,164],"complexity.":[69],"To":[70],"address":[71],"this":[72,74],"issue,":[73],"paper":[75],"proposes":[76],"clustering-based":[79],"pyramid":[80],"network":[82],"(SCPSN)":[83],"progressively":[85],"HRHSI":[87],"at":[88],"different":[89],"scales.":[90],"In":[91,264],"each":[92],"layer,":[95],"clustering":[97,104,145],"block":[99,105,111,116,184,198],"(CSRB)":[100],"consisting":[101],"(SCB),":[106],"patch":[107,181],"non":[108],"local":[109],"attention":[110,183],"(PNAB),":[112],"dynamic":[114,196],"fusion":[115,197],"(DFB)":[117,199],"is":[118,140,186,200,245],"designed":[119,201],"achieve":[121,144],"detail":[125],"features.":[126],"Specifically,":[127],"high":[130],"correlation":[131],"between":[132,214],"bands":[135],"LRHSI,":[137],"SCB":[139],"first":[141],"constructed":[142,187],"filtering":[150],"hyperchannels.":[152,193],"This":[153],"can":[154],"reduce":[155],"complexity":[165],"model.":[168],"Then,":[169],"by":[170,211],"utilizing":[171],"non-local":[173,182],"similarity":[174],"within":[177],"channel,":[179],"(PNAB)":[185],"enhance":[189],"Next,":[194],"establishing":[212],"correlations":[213],"enhanced":[215],"hyperchannels":[216],"other":[218,251,277],"channels.":[219],"Finally,":[220],"reconstructed":[222,235],"are":[224],"upsampled":[225],"added":[227],"corresponding":[230],"obtain":[233],"HRHSI.":[236],"Extensive":[237],"experiments":[238],"validate":[239],"that":[240,248],"performance":[242],"SCPSN":[244],"superior":[246],"some":[250],"state-of-the-art":[252],"(SOTA)":[253],"HSSR":[254],"terms":[257],"visual":[259],"effects":[260],"quantitative":[262],"metrics.":[263],"addition,":[265],"our":[266],"does":[268],"require":[270],"training":[271],"on":[272,286],"large-scale":[273],"datasets":[274],"compared":[275],"methods.":[278],"The":[279],"dataset":[280],"code":[282],"will":[283],"be":[284],"released":[285],"GitHub.":[287]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}