{"id":"https://openalex.org/W2511530320","doi":"https://doi.org/10.1109/icip.2016.7532932","title":"Local denoising based on curvature smoothing can visually outperform non-local methods on photographs with actual noise","display_name":"Local denoising based on curvature smoothing can visually outperform non-local methods on photographs with actual noise","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2511530320","doi":"https://doi.org/10.1109/icip.2016.7532932","mag":"2511530320"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7532932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532932","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10230/41638","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049833512","display_name":"Gabriela Ghimpe\u0163eanu","orcid":"https://orcid.org/0000-0001-6005-4703"},"institutions":[{"id":"https://openalex.org/I170486558","display_name":"Pompeu Fabra University","ror":"https://ror.org/04n0g0b29","country_code":"ES","type":"education","lineage":["https://openalex.org/I170486558"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Gabriela Ghimpeteanu","raw_affiliation_strings":["Dept. de Tecnologies de la Informaci\u00f3 i les Comunicacions, Universitat Pompeu Fabra, Spain"],"affiliations":[{"raw_affiliation_string":"Dept. de Tecnologies de la Informaci\u00f3 i les Comunicacions, Universitat Pompeu Fabra, Spain","institution_ids":["https://openalex.org/I170486558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103483071","display_name":"David Kane","orcid":null},"institutions":[{"id":"https://openalex.org/I170486558","display_name":"Pompeu Fabra University","ror":"https://ror.org/04n0g0b29","country_code":"ES","type":"education","lineage":["https://openalex.org/I170486558"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"David Kane","raw_affiliation_strings":["Dept. de Tecnologies de la Informaci\u00f3 i les Comunicacions, Universitat Pompeu Fabra, Spain"],"affiliations":[{"raw_affiliation_string":"Dept. de Tecnologies de la Informaci\u00f3 i les Comunicacions, Universitat Pompeu Fabra, Spain","institution_ids":["https://openalex.org/I170486558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001000212","display_name":"Thomas Batard","orcid":"https://orcid.org/0000-0001-9335-0314"},"institutions":[{"id":"https://openalex.org/I170486558","display_name":"Pompeu Fabra University","ror":"https://ror.org/04n0g0b29","country_code":"ES","type":"education","lineage":["https://openalex.org/I170486558"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Thomas Batard","raw_affiliation_strings":["Dept. de Tecnologies de la Informaci\u00f3 i les Comunicacions, Universitat Pompeu Fabra, Spain"],"affiliations":[{"raw_affiliation_string":"Dept. de Tecnologies de la Informaci\u00f3 i les Comunicacions, Universitat Pompeu Fabra, Spain","institution_ids":["https://openalex.org/I170486558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018631987","display_name":"Stacey Levine","orcid":"https://orcid.org/0000-0001-6535-7535"},"institutions":[{"id":"https://openalex.org/I165102784","display_name":"Duquesne University","ror":"https://ror.org/02336z538","country_code":"US","type":"education","lineage":["https://openalex.org/I165102784"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stacey Levine","raw_affiliation_strings":["Department of Mathematics and Computer Science, Duquesne University, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, Duquesne University, USA","institution_ids":["https://openalex.org/I165102784"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010974959","display_name":"Marcelo Bertalm\u0131\u0301o","orcid":"https://orcid.org/0000-0002-1023-8325"},"institutions":[{"id":"https://openalex.org/I170486558","display_name":"Pompeu Fabra University","ror":"https://ror.org/04n0g0b29","country_code":"ES","type":"education","lineage":["https://openalex.org/I170486558"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Marcelo Bertalmio","raw_affiliation_strings":["Dept. de Tecnologies de la Informaci\u00f3 i les Comunicacions, Universitat Pompeu Fabra, Spain"],"affiliations":[{"raw_affiliation_string":"Dept. de Tecnologies de la Informaci\u00f3 i les Comunicacions, Universitat Pompeu Fabra, Spain","institution_ids":["https://openalex.org/I170486558"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5049833512"],"corresponding_institution_ids":["https://openalex.org/I170486558"],"apc_list":null,"apc_paid":null,"fwci":0.3378,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66438255,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"3111","last_page":"3115"},"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":0.9991999864578247,"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/T11105","display_name":"Advanced Image Processing Techniques","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"}}],"keywords":[{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.7222689986228943},{"id":"https://openalex.org/keywords/curvature","display_name":"Curvature","score":0.703629195690155},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.669005274772644},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6323821544647217},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6092692017555237},{"id":"https://openalex.org/keywords/non-local-means","display_name":"Non-local means","score":0.578156054019928},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5586082339286804},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5502965450286865},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.5388201475143433},{"id":"https://openalex.org/keywords/euclidean-geometry","display_name":"Euclidean geometry","score":0.46803051233291626},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4668598473072052},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.4343186020851135},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4189225435256958},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.4124453365802765},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37891459465026855},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3408169746398926},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1163949966430664},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.05412757396697998}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.7222689986228943},{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.703629195690155},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.669005274772644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6323821544647217},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6092692017555237},{"id":"https://openalex.org/C101453961","wikidata":"https://www.wikidata.org/wiki/Q7048948","display_name":"Non-local means","level":4,"score":0.578156054019928},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5586082339286804},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5502965450286865},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.5388201475143433},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.46803051233291626},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4668598473072052},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.4343186020851135},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4189225435256958},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.4124453365802765},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37891459465026855},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3408169746398926},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1163949966430664},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.05412757396697998}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip.2016.7532932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532932","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:recercat.cat:2072/356870","is_oa":true,"landing_page_url":"http://hdl.handle.net/10230/41638","pdf_url":null,"source":{"id":"https://openalex.org/S4306402147","display_name":"RECERCAT (Consorci de Serveis Universitaris de Catalunya)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210090028","host_organization_name":"Consorci de Serveis Universitaris de Catalunya","host_organization_lineage":["https://openalex.org/I4210090028"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:recercat.cat:2072/356870","is_oa":true,"landing_page_url":"http://hdl.handle.net/10230/41638","pdf_url":null,"source":{"id":"https://openalex.org/S4306402147","display_name":"RECERCAT (Consorci de Serveis Universitaris de Catalunya)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210090028","host_organization_name":"Consorci de Serveis Universitaris de Catalunya","host_organization_lineage":["https://openalex.org/I4210090028"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1591116419","https://openalex.org/W1964100169","https://openalex.org/W1975837059","https://openalex.org/W1997147589","https://openalex.org/W2011181254","https://openalex.org/W2026019078","https://openalex.org/W2037133587","https://openalex.org/W2041625018","https://openalex.org/W2056370875","https://openalex.org/W2058005980","https://openalex.org/W2100415658","https://openalex.org/W2103559027","https://openalex.org/W2113824004","https://openalex.org/W2132181908","https://openalex.org/W2136396015","https://openalex.org/W2137113506","https://openalex.org/W2159269332","https://openalex.org/W2195101915","https://openalex.org/W2296274957","https://openalex.org/W4235713725","https://openalex.org/W4302436815","https://openalex.org/W6679925227"],"related_works":["https://openalex.org/W2098237619","https://openalex.org/W3046917719","https://openalex.org/W2035842925","https://openalex.org/W1538114257","https://openalex.org/W2097073572","https://openalex.org/W2276539377","https://openalex.org/W2810018092","https://openalex.org/W2001438600","https://openalex.org/W4287081060","https://openalex.org/W3182043338"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,18,22,64],"fast,":[3],"local":[4],"denoising":[5,37],"method":[6,44],"where":[7],"the":[8,12,48,53,74],"Euclidean":[9],"curvature":[10],"of":[11,66,76],"noisy":[13],"image":[14,24,78],"is":[15,25],"approximated":[16],"in":[17],"regularizing":[19],"manner":[20],"and":[21,60,83],"clean":[23],"reconstructed":[26],"from":[27],"this":[28],"smoothed":[29],"curvature.":[30],"User":[31],"preference":[32],"tests":[33,71],"show":[34],"that":[35],"when":[36],"real":[38],"photographs":[39],"with":[40,47,88],"actual":[41],"noise":[42],"our":[43],"produces":[45],"results":[46],"same":[49],"visual":[50],"quality":[51,79],"as":[52],"more":[54],"sophisticated,":[55],"nonlocal":[56],"algorithms":[57],"Non-local":[58],"Means":[59],"BM3D,":[61],"but":[62],"at":[63],"fraction":[65],"their":[67],"computational":[68],"cost.":[69],"These":[70],"also":[72],"highlight":[73],"limitations":[75],"objective":[77],"metrics":[80],"like":[81],"PSNR":[82],"SSIM,":[84],"which":[85],"correlate":[86],"poorly":[87],"user":[89],"preference.":[90]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
