{"id":"https://openalex.org/W4415538867","doi":"https://doi.org/10.1145/3746027.3755161","title":"Exploring Global Correlations via Polarity Memory for Multispectral Demosaicing","display_name":"Exploring Global Correlations via Polarity Memory for Multispectral Demosaicing","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415538867","doi":"https://doi.org/10.1145/3746027.3755161"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755161","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd 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/A5056566616","display_name":"Mengzu Liu","orcid":"https://orcid.org/0009-0005-4067-2519"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengzu Liu","raw_affiliation_strings":["Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0009-0005-4067-2519","affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082709075","display_name":"Junwei Xu","orcid":"https://orcid.org/0000-0001-9375-5426"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junwei Xu","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0001-9375-5426","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tao Huang","orcid":"https://orcid.org/0009-0007-4378-8837"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Huang","raw_affiliation_strings":["Hangzhou Institute of Technology, Xidian University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-4378-8837","affiliations":[{"raw_affiliation_string":"Hangzhou Institute of Technology, Xidian University, Hangzhou, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055063141","display_name":"Fangfang Wu","orcid":"https://orcid.org/0000-0002-2358-0293"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangfang Wu","raw_affiliation_strings":["School of Computer Sciences and Technology, Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-2358-0293","affiliations":[{"raw_affiliation_string":"School of Computer Sciences and Technology, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082067789","display_name":"Le Dong","orcid":"https://orcid.org/0000-0003-1410-1534"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Dong","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-1410-1534","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354039","display_name":"Xin Li","orcid":"https://orcid.org/0000-0003-2067-2763"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["State University of New York at Albany, Albany, NY, USA"],"raw_orcid":"https://orcid.org/0000-0003-2067-2763","affiliations":[{"raw_affiliation_string":"State University of New York at Albany, Albany, NY, USA","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037310802","display_name":"Weisheng Dong","orcid":"https://orcid.org/0000-0002-9632-985X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weisheng Dong","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-9632-985X","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.39377343,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3722","last_page":"3730"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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"}},{"id":"https://openalex.org/T12050","display_name":"Optical Polarization and Ellipsometry","score":0.9955999851226807,"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"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9848999977111816,"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/multispectral-image","display_name":"Multispectral image","score":0.921999990940094},{"id":"https://openalex.org/keywords/undersampling","display_name":"Undersampling","score":0.6657000184059143},{"id":"https://openalex.org/keywords/multispectral-pattern-recognition","display_name":"Multispectral pattern recognition","score":0.5291000008583069},{"id":"https://openalex.org/keywords/polarity","display_name":"Polarity (international relations)","score":0.5259000062942505},{"id":"https://openalex.org/keywords/mosaic","display_name":"Mosaic","score":0.48170000314712524},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4661000072956085},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.4350000023841858}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.921999990940094},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7250000238418579},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6686999797821045},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.6657000184059143},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6049000024795532},{"id":"https://openalex.org/C104541649","wikidata":"https://www.wikidata.org/wiki/Q6935090","display_name":"Multispectral pattern recognition","level":3,"score":0.5291000008583069},{"id":"https://openalex.org/C2777361361","wikidata":"https://www.wikidata.org/wiki/Q1112585","display_name":"Polarity (international relations)","level":3,"score":0.5259000062942505},{"id":"https://openalex.org/C110739175","wikidata":"https://www.wikidata.org/wiki/Q133067","display_name":"Mosaic","level":2,"score":0.48170000314712524},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4661000072956085},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.4350000023841858},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40400001406669617},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4020000100135803},{"id":"https://openalex.org/C27624317","wikidata":"https://www.wikidata.org/wiki/Q263499","display_name":"Demosaicing","level":5,"score":0.3734000027179718},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35019999742507935},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.3082999885082245},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2930000126361847},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755161","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1597864587","https://openalex.org/W2058127401","https://openalex.org/W2136251662","https://openalex.org/W2144412886","https://openalex.org/W2327302159","https://openalex.org/W2588000623","https://openalex.org/W2604425999","https://openalex.org/W2770113520","https://openalex.org/W2906515941","https://openalex.org/W2911876518","https://openalex.org/W2963008638","https://openalex.org/W2990205821","https://openalex.org/W3041490661","https://openalex.org/W3140715649","https://openalex.org/W3193497103","https://openalex.org/W3207918547","https://openalex.org/W4225672218","https://openalex.org/W4282917395","https://openalex.org/W4285300354","https://openalex.org/W4387967903"],"related_works":[],"abstract_inverted_index":{"Multispectral":[0],"image":[1,25],"demosaicing":[2],"aims":[3],"to":[4,34,39,54,91,94,110],"reconstruct":[5],"full":[6],"band":[7],"multispectral":[8,24,61],"images":[9,62],"from":[10,63,84],"a":[11,88,121],"compressed":[12,64],"spectral":[13,65,99],"mosaic":[14,40,66],"images.":[15,67],"Although":[16],"existing":[17,107],"learning-based":[18],"methods":[19],"have":[20],"made":[21],"progress":[22],"in":[23,87,117],"demosaicing,":[26],"there":[27],"still":[28],"exist":[29],"intrinsic":[30],"performance":[31,146],"bottlenecks":[32],"due":[33],"the":[35,95],"heavy":[36],"undersampling":[37],"according":[38],"pattern.":[41],"To":[42],"address":[43],"this":[44],"issue,":[45],"we":[46,119],"propose":[47],"Polarity":[48,70],"memory":[49,71],"network":[50,72],"with":[51,101],"quant":[52,122,134],"attention":[53,123,137],"establish":[55],"global":[56],"correlation,":[57],"thus":[58],"reconstructing":[59],"high-quality":[60],"Our":[68],"proposed":[69],"adaptively":[73],"encapsulates":[74],"reconstruction-oriented":[75],"representations,":[76],"then":[77],"amplifies":[78],"relevant":[79],"ones":[80,86],"and":[81,151],"reducing":[82],"noise":[83],"irrelevant":[85],"polarity-aware":[89],"manner":[90],"better":[92,152],"cater":[93],"enhancement":[96],"of":[97],"different":[98],"information":[100],"linear":[102],"computational":[103],"complexity.":[104],"Moreover,":[105],"considering":[106],"methods'":[108],"inability":[109],"adequately":[111],"compensate":[112],"for":[113,136],"long":[114],"distance":[115],"interactions":[116],"reconstruction,":[118],"introduce":[120],"paradigm":[124],"that":[125],"categorize":[126],"tokens":[127],"into":[128],"semantic-aware":[129],"groups":[130],"using":[131],"an":[132],"efficient":[133],"operation":[135],"computation.":[138],"Experimental":[139],"results":[140,154],"show":[141],"our":[142],"method":[143],"achieves":[144],"state-of-the-art":[145],"on":[147,155],"various":[148],"simulation":[149],"datasets":[150],"vision":[153],"real-world":[156],"datasets.":[157]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-25T00:00:00"}
