{"id":"https://openalex.org/W4382322625","doi":"https://doi.org/10.1109/access.2023.3273486","title":"Deep Convolutional Network Aided by Non-Local Method for Hyperspectral Image Denoising","display_name":"Deep Convolutional Network Aided by Non-Local Method for Hyperspectral Image Denoising","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4382322625","doi":"https://doi.org/10.1109/access.2023.3273486"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3273486","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3273486","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2023.3273486","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107638201","display_name":"Gabriel A. De Oliveira","orcid":"https://orcid.org/0009-0005-8238-5067"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Gabriel A. De Oliveira","raw_affiliation_strings":["DECOM/FEEC, University of Campinas, São Paulo, Campinas, Brazil"],"raw_orcid":"https://orcid.org/0009-0005-8238-5067","affiliations":[{"raw_affiliation_string":"DECOM/FEEC, University of Campinas, São Paulo, Campinas, Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023714534","display_name":"Larissa Medeiros de Almeida","orcid":"https://orcid.org/0000-0003-3567-5131"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Larissa Medeiros De Almeida","raw_affiliation_strings":["Transmissora Aliança de Energia Elétrica S.A.-TAESA, Rio de Janeiro, Brazil"],"raw_orcid":"https://orcid.org/0000-0003-3567-5131","affiliations":[{"raw_affiliation_string":"Transmissora Aliança de Energia Elétrica S.A.-TAESA, Rio de Janeiro, Brazil","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051507029","display_name":"Eduardo Rodrigues de Lima","orcid":"https://orcid.org/0000-0003-4268-9726"},"institutions":[{"id":"https://openalex.org/I4210119805","display_name":"Instituto de Pesca","ror":"https://ror.org/02gcdp811","country_code":"BR","type":"facility","lineage":["https://openalex.org/I4210119805"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Eduardo R. De Lima","raw_affiliation_strings":["Department of Hardware Design, Instituto de Pesquisas Eldorado, São Paulo, Campinas, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Hardware Design, Instituto de Pesquisas Eldorado, São Paulo, Campinas, Brazil","institution_ids":["https://openalex.org/I4210119805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014920481","display_name":"Lu\u00eds Geraldo P. Meloni","orcid":"https://orcid.org/0000-0002-5782-9608"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Lu\u00eds Geraldo P. Meloni","raw_affiliation_strings":["DECOM/FEEC, University of Campinas, São Paulo, Campinas, Brazil"],"raw_orcid":"https://orcid.org/0000-0002-5782-9608","affiliations":[{"raw_affiliation_string":"DECOM/FEEC, University of Campinas, São Paulo, Campinas, Brazil","institution_ids":["https://openalex.org/I181391015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.7859,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.73713013,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"45233","last_page":"45242"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998999834060669,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9997000098228455,"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":0.9954000115394592,"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":0.7488545179367065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7311438918113708},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7140146493911743},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6871508359909058},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6621615886688232},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6350595355033875},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5855971574783325},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5644407868385315},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.5308927893638611},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3975427448749542},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.26451176404953003},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.26184600591659546}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7488545179367065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7311438918113708},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7140146493911743},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6871508359909058},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6621615886688232},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6350595355033875},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5855971574783325},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5644407868385315},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.5308927893638611},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3975427448749542},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26451176404953003},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26184600591659546},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3273486","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3273486","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8fcb3426f8a84f228f6905814e86048e","is_oa":true,"landing_page_url":"https://doaj.org/article/8fcb3426f8a84f228f6905814e86048e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 45233-45242 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3273486","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3273486","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W609694675","https://openalex.org/W1974438823","https://openalex.org/W2010319424","https://openalex.org/W2056370875","https://openalex.org/W2087660735","https://openalex.org/W2133665775","https://openalex.org/W2138621882","https://openalex.org/W2157963512","https://openalex.org/W2499334499","https://openalex.org/W2508457857","https://openalex.org/W2520430674","https://openalex.org/W2562637781","https://openalex.org/W2764207251","https://openalex.org/W2765366036","https://openalex.org/W2767511704","https://openalex.org/W2782517596","https://openalex.org/W2790888198","https://openalex.org/W2793218933","https://openalex.org/W2793272303","https://openalex.org/W2799450452","https://openalex.org/W2806155925","https://openalex.org/W2921072760","https://openalex.org/W2951443864","https://openalex.org/W2960360058","https://openalex.org/W2964125708","https://openalex.org/W3013064625","https://openalex.org/W3021581008","https://openalex.org/W3048631361","https://openalex.org/W3098435832","https://openalex.org/W3102692100","https://openalex.org/W3184720854","https://openalex.org/W4231606319","https://openalex.org/W4253964759","https://openalex.org/W4310260446","https://openalex.org/W6640723650","https://openalex.org/W6776769650"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2060875994","https://openalex.org/W2027399350","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440"],"abstract_inverted_index":{"This":[0,86],"paper":[1,156],"introduces":[2],"a":[3,38,53,57,77,137,186],"new":[4],"hyperspectral":[5,169,191],"image":[6,163],"denoising":[7,167],"method":[8],"called":[9],"Non-local":[10],"Convolutional":[11,58],"Neural":[12,59],"Network":[13],"Denoiser":[14],"(NL-CNND).":[15],"The":[16,100,155,175],"technique":[17,88],"exploits":[18],"data":[19,194],"in":[20,52],"four":[21],"bands":[22,46],"adjacent":[23],"to":[24,80,93,106],"the":[25,32,45,66,69,73,119,134,145,151],"target":[26],"one":[27,64],"as":[28],"additional":[29],"information":[30],"for":[31,161,166,179],"restoring":[33],"process,":[34],"and":[35,97,112,129,197],"it":[36],"uses":[37],"pre-denoising":[39],"step":[40,55],"based":[41,184],"on":[42,150,185],"BM4D.":[43],"All":[44],"paired":[47],"with":[48,82],"their":[49,173],"pre-denoised":[50],"versions":[51],"second":[54],"feed":[56],"Network.":[60],"To":[61],"network":[62,180],"generalization,":[63],"of":[65,72,140,172,189],"inputs":[67],"is":[68,182],"noise":[70,84,107],"level":[71,139],"input":[74,152],"image,":[75],"allowing":[76,165],"single":[78],"model":[79],"work":[81],"different":[83],"levels.":[85],"restoration":[87,121],"overcomes":[89],"quality":[90],"when":[91],"compared":[92],"current":[94],"eight":[95],"classical":[96],"neural":[98],"methods.":[99],"results":[101,135],"show":[102,136],"higher":[103,138],"peak":[104],"signal":[105],"ratio,":[108],"structural":[109],"similarity":[110],"index,":[111],"spectral":[113],"angle":[114],"mapper":[115],"metrics":[116],"than":[117],"all":[118],"other":[120],"methods,":[122],"surpassing":[123],"those":[124],"achieved":[125],"using":[126],"Block":[127],"Matching":[128],"4D":[130],"Filtering":[131],"alone.":[132],"Besides,":[133],"detail":[141],"visually":[142],"while":[143],"at":[144],"same":[146],"time":[147],"reducing":[148],"over-smoothing":[149],"images\u2019":[153],"features.":[154],"also":[157],"includes":[158],"an":[159],"algorithm":[160],"complete":[162],"restoration,":[164],"full-sized":[168],"images":[170],"independent":[171],"shape.":[174],"dataset":[176],"creation":[177],"used":[178],"training":[181],"detailed,":[183],"small":[187],"set":[188],"available":[190],"images,":[192],"encompassing":[193],"normalization,":[195],"conversion,":[196],"storage.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}