{"id":"https://openalex.org/W2029192468","doi":"https://doi.org/10.1117/12.2042396","title":"Generalized non-local means filtering for image denoising","display_name":"Generalized non-local means filtering for image denoising","publication_year":2014,"publication_date":"2014-02-25","ids":{"openalex":"https://openalex.org/W2029192468","doi":"https://doi.org/10.1117/12.2042396","mag":"2029192468"},"language":"en","primary_location":{"id":"doi:10.1117/12.2042396","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2042396","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/A5021030041","display_name":"Sudipto Dolui","orcid":"https://orcid.org/0000-0002-9035-3795"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]},{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sudipto Dolui","raw_affiliation_strings":["Univ. of Pennsylvania (United States)","University of Pennsylvania UNITED STATES"],"affiliations":[{"raw_affiliation_string":"Univ. of Pennsylvania (United States)","institution_ids":["https://openalex.org/I36788626"]},{"raw_affiliation_string":"University of Pennsylvania UNITED STATES","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012376947","display_name":"Iv\u00e1n C. Salgado Patarroyo","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Iv\u00e1n C. Salgado Patarroyo","raw_affiliation_strings":["Univ. of Waterloo (Canada)","University of Waterloo-Canad\u00e1"],"affiliations":[{"raw_affiliation_string":"Univ. of Waterloo (Canada)","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"University of Waterloo-Canad\u00e1","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060926838","display_name":"Oleg Michailovich","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Oleg V. Michailovich","raw_affiliation_strings":["Univ. of Waterloo (Canada)","University of Waterloo-Canad\u00e1"],"affiliations":[{"raw_affiliation_string":"Univ. of Waterloo (Canada)","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"University of Waterloo-Canad\u00e1","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021030041"],"corresponding_institution_ids":["https://openalex.org/I36788626","https://openalex.org/I79576946"],"apc_list":null,"apc_paid":null,"fwci":0.2439,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57938217,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"9019","issue":null,"first_page":"90190B","last_page":"90190B"},"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":0.9944000244140625,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9876000285148621,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/computer-science","display_name":"Computer science","score":0.7239287495613098},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6484639644622803},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6359796524047852},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6265921592712402},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6106460094451904},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.5927489995956421},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5725101232528687},{"id":"https://openalex.org/keywords/unification","display_name":"Unification","score":0.4896557927131653},{"id":"https://openalex.org/keywords/value-noise","display_name":"Value noise","score":0.46845293045043945},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4656532406806946},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.4618043303489685},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4506233334541321},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4491182267665863},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44243180751800537},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.43746697902679443},{"id":"https://openalex.org/keywords/gradient-noise","display_name":"Gradient noise","score":0.43504413962364197},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38378024101257324},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29667776823043823},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.17201167345046997}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7239287495613098},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6484639644622803},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6359796524047852},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6265921592712402},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6106460094451904},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.5927489995956421},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5725101232528687},{"id":"https://openalex.org/C96146094","wikidata":"https://www.wikidata.org/wiki/Q609057","display_name":"Unification","level":2,"score":0.4896557927131653},{"id":"https://openalex.org/C182163834","wikidata":"https://www.wikidata.org/wiki/Q2926529","display_name":"Value noise","level":5,"score":0.46845293045043945},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4656532406806946},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.4618043303489685},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4506233334541321},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4491182267665863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44243180751800537},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.43746697902679443},{"id":"https://openalex.org/C200378446","wikidata":"https://www.wikidata.org/wiki/Q4147391","display_name":"Gradient noise","level":5,"score":0.43504413962364197},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38378024101257324},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29667776823043823},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.17201167345046997},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C187612029","wikidata":"https://www.wikidata.org/wiki/Q17083130","display_name":"Noise floor","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2042396","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2042396","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W212537071","https://openalex.org/W1494195692","https://openalex.org/W1593077517","https://openalex.org/W1980949712","https://openalex.org/W1995481051","https://openalex.org/W2000953144","https://openalex.org/W2010491386","https://openalex.org/W2028586667","https://openalex.org/W2034973332","https://openalex.org/W2056370875","https://openalex.org/W2070627872","https://openalex.org/W2073660032","https://openalex.org/W2075200603","https://openalex.org/W2097073572","https://openalex.org/W2133665775","https://openalex.org/W2136396015","https://openalex.org/W2142592339","https://openalex.org/W2144462989","https://openalex.org/W2144851790","https://openalex.org/W2146422493","https://openalex.org/W2160637922","https://openalex.org/W2160748123","https://openalex.org/W2170608748","https://openalex.org/W2500481016","https://openalex.org/W3121742466","https://openalex.org/W3122764147","https://openalex.org/W6635236853","https://openalex.org/W6645437957","https://openalex.org/W6649363835","https://openalex.org/W6653185293","https://openalex.org/W6664401941","https://openalex.org/W6674723063","https://openalex.org/W6680017387","https://openalex.org/W6681493674","https://openalex.org/W6681771927","https://openalex.org/W6788344770","https://openalex.org/W6788654838"],"related_works":["https://openalex.org/W3125397569","https://openalex.org/W145422376","https://openalex.org/W4226451553","https://openalex.org/W2116036791","https://openalex.org/W2588855097","https://openalex.org/W2032021057","https://openalex.org/W2057119739","https://openalex.org/W2150834232","https://openalex.org/W3149431777","https://openalex.org/W1572192126"],"abstract_inverted_index":{"Non-local":[0],"means":[1],"(NLM)":[2],"filtering":[3,66],"has":[4],"been":[5,26],"shown":[6],"to":[7,28,34,90,113,132,138],"outperform":[8],"alternative":[9],"denoising":[10],"methodologies":[11],"under":[12],"the":[13,70,78,91,94,103,119,122,125,156,161,175,179],"model":[14],"of":[15,32,38,43,72,80,93,105,118,121,128,148,160,170,178],"additive":[16],"white":[17],"Gaussian":[18],"noise":[19,39,52,62,99,172],"contamination.":[20],"Recently,":[21],"several":[22],"theoretical":[23,150],"frameworks":[24,45],"have":[25],"developed":[27],"extend":[29],"this":[30,129],"class":[31],"algorithms":[33],"more":[35],"general":[36],"types":[37],"statistics.":[40,63],"However,":[41],"many":[42],"these":[44],"are":[46,56,165],"specifically":[47],"designed":[48],"for":[49,97,167],"a":[50,73,106,134,141,168],"single":[51],"contamination":[53],"model,":[54],"and":[55,151,174],"far":[57],"from":[58],"optimal":[59],"across":[60],"varying":[61],"The":[64,88],"NLM":[65,95],"techniques":[67],"rely":[68],"on":[69],"definition":[71,104],"similarity":[74,79,108,143,163,181],"measure,":[75,144],"which":[76,110],"quantifies":[77],"two":[81],"neighbourhoods":[82],"along":[83],"with":[84],"their":[85],"respective":[86],"centroids.":[87],"key":[89],"unification":[92],"filter":[96],"different":[98],"statistics":[100,120],"lies":[101],"in":[102],"universal":[107,142],"measure":[109,164,182],"is":[111,131,183],"guaranteed":[112],"provide":[114,133],"favourable":[115,153],"performance":[116],"irrespective":[117],"noise.":[123],"Accordingly,":[124],"main":[126],"contribution":[127],"work":[130],"rigorous":[135],"statistical":[136],"framework":[137],"derive":[139],"such":[140],"while":[145],"highlighting":[146],"some":[147],"its":[149],"practical":[152,176],"characteristics.":[154],"Additionally,":[155],"closed":[157],"form":[158],"expressions":[159],"proposed":[162,180],"provided":[166],"number":[169],"important":[171],"scenarios":[173],"utility":[177],"demonstrated":[184],"through":[185],"numerical":[186],"experiments.":[187]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}