{"id":"https://openalex.org/W2991209609","doi":"https://doi.org/10.1109/tgrs.2019.2952062","title":"A Single Model CNN for Hyperspectral Image Denoising","display_name":"A Single Model CNN for Hyperspectral Image Denoising","publication_year":2019,"publication_date":"2019-11-26","ids":{"openalex":"https://openalex.org/W2991209609","doi":"https://doi.org/10.1109/tgrs.2019.2952062","mag":"2991209609"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2019.2952062","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2019.2952062","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":"https://openalex.org/A5017808366","display_name":"Alessandro Maffei","orcid":null},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Alessandro Maffei","raw_affiliation_strings":["Department of Information Engineering and Computer Science, Remote Sensing Laboratory, University of Trento, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, Remote Sensing Laboratory, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039673511","display_name":"Juan M. Haut","orcid":"https://orcid.org/0000-0001-6701-961X"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan M. Haut","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046123228","display_name":"Mercedes E. Paoletti","orcid":"https://orcid.org/0000-0003-1030-3729"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Mercedes Eugenia Paoletti","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010624980","display_name":"Javier Plaza","orcid":"https://orcid.org/0000-0002-2384-9141"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Javier Plaza","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006095323","display_name":"Lorenzo Bruzzone","orcid":"https://orcid.org/0000-0002-6036-459X"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Lorenzo Bruzzone","raw_affiliation_strings":["Department of Information Engineering and Computer Science, Remote Sensing Laboratory, University of Trento, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, Remote Sensing Laboratory, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054292278","display_name":"Antonio Plaza","orcid":"https://orcid.org/0000-0002-9613-1659"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio Plaza","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5017808366"],"corresponding_institution_ids":["https://openalex.org/I193223587"],"apc_list":null,"apc_paid":null,"fwci":5.8245,"has_fulltext":false,"cited_by_count":158,"citation_normalized_percentile":{"value":0.96949437,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"58","issue":"4","first_page":"2516","last_page":"2529"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9998000264167786,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9994000196456909,"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":0.8247666358947754},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7380495071411133},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7348145842552185},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6919764280319214},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6356766223907471},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5796699523925781},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.567379355430603},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43274030089378357},{"id":"https://openalex.org/keywords/data-cube","display_name":"Data cube","score":0.42282021045684814},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33921748399734497},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22946441173553467},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.15094122290611267}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8247666358947754},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7380495071411133},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7348145842552185},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6919764280319214},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6356766223907471},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5796699523925781},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.567379355430603},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43274030089378357},{"id":"https://openalex.org/C78168278","wikidata":"https://www.wikidata.org/wiki/Q5227269","display_name":"Data cube","level":2,"score":0.42282021045684814},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33921748399734497},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22946441173553467},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.15094122290611267}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2019.2952062","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2019.2952062","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:iris.unitn.it:11572/287656","is_oa":false,"landing_page_url":"http://hdl.handle.net/11572/287656","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"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":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G4453694436","display_name":null,"funder_award_id":"734541","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"},{"id":"https://openalex.org/G8872719428","display_name":null,"funder_award_id":"FPU14/02012-FPU15/02090","funder_id":"https://openalex.org/F4320321764","funder_display_name":"Ministerio de Educaci\u00f3n, Cultura y Deporte"}],"funders":[{"id":"https://openalex.org/F4320321764","display_name":"Ministerio de Educaci\u00f3n, Cultura y Deporte","ror":"https://ror.org/03nc27g21"},{"id":"https://openalex.org/F4320325115","display_name":"Consejer\u00eda de Educaci\u00f3n y Empleo, Junta de Extremadura","ror":"https://ror.org/02a6ezh03"},{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W199564985","https://openalex.org/W1522301498","https://openalex.org/W1665214252","https://openalex.org/W1709548961","https://openalex.org/W1849277567","https://openalex.org/W1928626817","https://openalex.org/W1973895663","https://openalex.org/W1974438823","https://openalex.org/W1994040806","https://openalex.org/W2020787092","https://openalex.org/W2029316659","https://openalex.org/W2036097478","https://openalex.org/W2039596145","https://openalex.org/W2048695508","https://openalex.org/W2053514113","https://openalex.org/W2056370875","https://openalex.org/W2069231830","https://openalex.org/W2070262806","https://openalex.org/W2076063813","https://openalex.org/W2090424610","https://openalex.org/W2117767750","https://openalex.org/W2129891925","https://openalex.org/W2133665775","https://openalex.org/W2136467648","https://openalex.org/W2160484748","https://openalex.org/W2163605009","https://openalex.org/W2237974960","https://openalex.org/W2336104109","https://openalex.org/W2508457857","https://openalex.org/W2556872594","https://openalex.org/W2764207251","https://openalex.org/W2765366036","https://openalex.org/W2765983529","https://openalex.org/W2782517596","https://openalex.org/W2789224430","https://openalex.org/W2790528326","https://openalex.org/W2792897399","https://openalex.org/W2793218933","https://openalex.org/W2799390666","https://openalex.org/W2804532080","https://openalex.org/W2806155925","https://openalex.org/W2806966882","https://openalex.org/W2898381489","https://openalex.org/W2906893282","https://openalex.org/W2919115771","https://openalex.org/W2949194345","https://openalex.org/W2964121744","https://openalex.org/W3098435832","https://openalex.org/W3101640299","https://openalex.org/W3104725225","https://openalex.org/W4240485910","https://openalex.org/W4383097851","https://openalex.org/W6608171436","https://openalex.org/W6631190155","https://openalex.org/W6637242042","https://openalex.org/W6637616945","https://openalex.org/W6639204139","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W1982418987","https://openalex.org/W3112209948","https://openalex.org/W2889956472","https://openalex.org/W3178760882","https://openalex.org/W2039721451","https://openalex.org/W2055440460","https://openalex.org/W1556234160","https://openalex.org/W2053822900","https://openalex.org/W2165515632","https://openalex.org/W2001084846"],"abstract_inverted_index":{"Denoising":[0],"is":[1,76],"a":[2],"common":[3],"preprocessing":[4],"step":[5],"prior":[6],"to":[7,64],"the":[8,17,53,69,113,131],"analysis":[9],"and":[10,115,126],"interpretation":[11],"of":[12,20],"hyperspectral":[13],"images":[14],"(HSIs).":[15],"However,":[16],"vast":[18],"majority":[19],"methods":[21,47],"typically":[22],"adopted":[23],"for":[24,31],"HSI":[25,41,97,103,137],"denoising":[26,66,105,138],"exploit":[27],"architectures":[28],"originally":[29],"developed":[30],"grayscale":[32],"or":[33],"RGB":[34],"images,":[35],"exhibiting":[36],"limitations":[37],"when":[38],"processing":[39],"high-dimensional":[40],"data":[42,128],"cubes.":[43],"In":[44],"particular,":[45],"traditional":[46],"do":[48],"not":[49,77],"take":[50],"into":[51,110],"account":[52],"high":[54],"spectral":[55,71,116],"correlation":[56],"between":[57],"adjacent":[58],"bands":[59],"in":[60,74,119],"HSIs,":[61],"which":[62],"leads":[63],"unsatisfactory":[65],"performance":[67],"as":[68,90],"rich":[70],"information":[72,117],"present":[73],"HSIs":[75],"fully":[78],"exploited.":[79],"To":[80],"overcome":[81],"this":[82,84],"limitation,":[83],"article":[85],"considers":[86],"deep":[87],"learning":[88],"models-such":[89],"convolutional":[91],"neural":[92],"networks":[93],"(CNNs)-to":[94],"perform":[95],"spectral-spatial":[96],"denoising.":[98],"The":[99],"proposed":[100,132],"model,":[101],"called":[102],"single":[104],"CNN":[106],"(HSI-SDeCNN),":[107],"efficiently":[108],"takes":[109],"consideration":[111],"both":[112,124],"spatial":[114],"contained":[118],"HSIs.":[120],"Experimental":[121],"results":[122],"on":[123],"synthetic":[125],"real":[127],"demonstrate":[129],"that":[130],"HSI-SDeCNN":[133],"outperforms":[134],"other":[135],"state-of-the-art":[136],"methods.":[139],"Source":[140],"code:":[141],"https://github.com/mhaut/HSI-SDeCNN.":[142]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":40},{"year":2022,"cited_by_count":27},{"year":2021,"cited_by_count":23},{"year":2020,"cited_by_count":7}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}