{"id":"https://openalex.org/W2950650271","doi":"https://doi.org/10.1109/tip.2020.2980116","title":"NLH: A Blind Pixel-Level Non-Local Method for Real-World Image Denoising","display_name":"NLH: A Blind Pixel-Level Non-Local Method for Real-World Image Denoising","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2950650271","doi":"https://doi.org/10.1109/tip.2020.2980116","mag":"2950650271"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2020.2980116","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.2980116","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1906.06834","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yingkun Hou","orcid":"https://orcid.org/0000-0003-2153-9040"},"institutions":[{"id":"https://openalex.org/I4210118050","display_name":"Taishan University","ror":"https://ror.org/02bpnkx55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210118050"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingkun Hou","raw_affiliation_strings":["School of Information Science and Technology, Taishan University, Tai\u2019an, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Taishan University, Tai\u2019an, China","institution_ids":["https://openalex.org/I4210118050"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jun Xu","orcid":"https://orcid.org/0000-0002-1602-538X"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Xu","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mingxia Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingxia Liu","raw_affiliation_strings":["School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, USA"],"affiliations":[{"raw_affiliation_string":"School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, USA","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Guanghai Liu","orcid":"https://orcid.org/0000-0002-1558-2694"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanghai Liu","raw_affiliation_strings":["School of Computer Science and Information Technology, Guangxi Normal University, Guilin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Technology, Guangxi Normal University, Guilin, China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Li Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113480","display_name":"Mohamed bin Zayed University of Artificial Intelligence","ror":"https://ror.org/0258gkt32","country_code":"AE","type":"education","lineage":["https://openalex.org/I4210113480"]},{"id":"https://openalex.org/I4210116052","display_name":"Inception Institute of Artificial Intelligence","ror":"https://ror.org/02664zk40","country_code":"AE","type":"facility","lineage":["https://openalex.org/I4210116052"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Li Liu","raw_affiliation_strings":["Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates","Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates"],"affiliations":[{"raw_affiliation_string":"Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210116052"]},{"raw_affiliation_string":"Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210113480"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Fan Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113480","display_name":"Mohamed bin Zayed University of Artificial Intelligence","ror":"https://ror.org/0258gkt32","country_code":"AE","type":"education","lineage":["https://openalex.org/I4210113480"]},{"id":"https://openalex.org/I4210116052","display_name":"Inception Institute of Artificial Intelligence","ror":"https://ror.org/02664zk40","country_code":"AE","type":"facility","lineage":["https://openalex.org/I4210116052"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Fan Zhu","raw_affiliation_strings":["Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates","Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates"],"affiliations":[{"raw_affiliation_string":"Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210116052"]},{"raw_affiliation_string":"Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210113480"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ling Shao","orcid":"https://orcid.org/0000-0002-8264-6117"},"institutions":[{"id":"https://openalex.org/I4210113480","display_name":"Mohamed bin Zayed University of Artificial Intelligence","ror":"https://ror.org/0258gkt32","country_code":"AE","type":"education","lineage":["https://openalex.org/I4210113480"]},{"id":"https://openalex.org/I4210116052","display_name":"Inception Institute of Artificial Intelligence","ror":"https://ror.org/02664zk40","country_code":"AE","type":"facility","lineage":["https://openalex.org/I4210116052"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Ling Shao","raw_affiliation_strings":["Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates","Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates"],"affiliations":[{"raw_affiliation_string":"Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210116052"]},{"raw_affiliation_string":"Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210113480"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210118050"],"apc_list":null,"apc_paid":null,"fwci":4.8092,"has_fulltext":false,"cited_by_count":89,"citation_normalized_percentile":{"value":0.96071085,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"29","issue":null,"first_page":"5121","last_page":"5135"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.934499979019165,"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":0.934499979019165,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.005900000222027302,"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"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.005499999970197678,"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/pixel","display_name":"Pixel","score":0.6654999852180481},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6513000130653381},{"id":"https://openalex.org/keywords/non-local-means","display_name":"Non-local means","score":0.6137999892234802},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.597100019454956},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5049999952316284},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.499099999666214},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.49559998512268066},{"id":"https://openalex.org/keywords/video-denoising","display_name":"Video denoising","score":0.438400000333786},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.42660000920295715}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7936000227928162},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6654999852180481},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6513000130653381},{"id":"https://openalex.org/C101453961","wikidata":"https://www.wikidata.org/wiki/Q7048948","display_name":"Non-local means","level":4,"score":0.6137999892234802},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6053000092506409},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.597100019454956},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5566999912261963},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5049999952316284},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.499099999666214},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.49559998512268066},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.438400000333786},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.42660000920295715},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4244999885559082},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3817000091075897},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.3758000135421753},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.35510000586509705},{"id":"https://openalex.org/C18537770","wikidata":"https://www.wikidata.org/wiki/Q25523","display_name":"Wiener filter","level":2,"score":0.34630000591278076},{"id":"https://openalex.org/C187029792","wikidata":"https://www.wikidata.org/wiki/Q2179112","display_name":"Haar","level":3,"score":0.32420000433921814},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.3018999993801117},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2955000102519989},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2773999869823456},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2624000012874603},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2529999911785126}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2020.2980116","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.2980116","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1906.06834","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.06834","pdf_url":"https://arxiv.org/pdf/1906.06834","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1906.06834","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.06834","pdf_url":"https://arxiv.org/pdf/1906.06834","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6327050509","display_name":null,"funder_award_id":"61866005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6960857768","display_name":null,"funder_award_id":"61379015","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7156112097","display_name":null,"funder_award_id":"61620106008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1504409388","https://openalex.org/W1906770428","https://openalex.org/W1978749115","https://openalex.org/W1986830331","https://openalex.org/W1993120651","https://openalex.org/W2009548700","https://openalex.org/W2014311222","https://openalex.org/W2023005931","https://openalex.org/W2047710600","https://openalex.org/W2051187242","https://openalex.org/W2056370875","https://openalex.org/W2097073572","https://openalex.org/W2114122776","https://openalex.org/W2116013899","https://openalex.org/W2117188745","https://openalex.org/W2130184048","https://openalex.org/W2133665775","https://openalex.org/W2136035751","https://openalex.org/W2153663612","https://openalex.org/W2159736423","https://openalex.org/W2164647001","https://openalex.org/W2172275395","https://openalex.org/W2207282238","https://openalex.org/W2219841864","https://openalex.org/W2469031810","https://openalex.org/W2474817805","https://openalex.org/W2505029951","https://openalex.org/W2508457857","https://openalex.org/W2534320940","https://openalex.org/W2536599074","https://openalex.org/W2539781702","https://openalex.org/W2613184245","https://openalex.org/W2764207251","https://openalex.org/W2766398684","https://openalex.org/W2798278116","https://openalex.org/W2798427787","https://openalex.org/W2798724920","https://openalex.org/W2799192307","https://openalex.org/W2799265886","https://openalex.org/W2820727372","https://openalex.org/W2912435603","https://openalex.org/W2962767526","https://openalex.org/W2963200935","https://openalex.org/W2963315679","https://openalex.org/W2963686971","https://openalex.org/W2963725279","https://openalex.org/W2964013315","https://openalex.org/W2964046397","https://openalex.org/W2964116203","https://openalex.org/W2971719842","https://openalex.org/W2999653953","https://openalex.org/W3011440129","https://openalex.org/W4251101141","https://openalex.org/W6629134395","https://openalex.org/W6726381175","https://openalex.org/W6734932694","https://openalex.org/W6749894445","https://openalex.org/W6758205271","https://openalex.org/W6772307453","https://openalex.org/W6783508261"],"related_works":[],"abstract_inverted_index":{"Non-local":[0],"self":[1],"similarity":[2],"(NSS)":[3],"is":[4,23,51,61,129,145],"a":[5,24,38,47,96],"powerful":[6],"prior":[7],"of":[8,15],"natural":[9,68],"images":[10],"for":[11],"image":[12,76,98,141],"denoising.":[13,142],"Most":[14],"existing":[16,133],"denoising":[17,77,99],"methods":[18,138],"employ":[19],"similar":[20,44,59,65],"patches,":[21],"which":[22,70],"patch-level":[25],"NSS":[26,40,83],"prior.":[27],"In":[28],"this":[29],"paper,":[30],"we":[31,85],"take":[32],"one":[33],"step":[34],"forward":[35],"by":[36,53],"introducing":[37],"pixel-level":[39,82],"prior,":[41,84],"i.e.,":[42],"searching":[43],"pixels":[45,60],"across":[46],"non-local":[48],"region.":[49],"This":[50],"motivated":[52],"the":[54,80,103,117],"fact":[55],"that":[56],"finding":[57],"closely":[58],"more":[62],"feasible":[63],"than":[64,124],"patches":[66],"in":[67],"images,":[69],"can":[71],"be":[72],"used":[73],"to":[74],"enhance":[75],"performance.":[78],"With":[79],"introduced":[81],"propose":[86],"an":[87],"accurate":[88],"noise":[89],"level":[90],"estimation":[91],"method,":[92],"and":[93,107,128],"then":[94],"develop":[95],"blind":[97],"method":[100,119],"based":[101,137],"on":[102,112,139],"lifting":[104],"Haar":[105],"transform":[106],"Wiener":[108],"filtering":[109],"techniques.":[110],"Experiments":[111],"benchmark":[113],"datasets":[114],"demonstrate":[115],"that,":[116],"proposed":[118],"achieves":[120],"much":[121],"better":[122],"performance":[123],"previous":[125],"non-deep":[126],"methods,":[127],"still":[130],"competitive":[131],"with":[132],"state-of-the-art":[134],"deep":[135],"learning":[136],"real-world":[140],"The":[143],"code":[144],"publicly":[146],"available":[147],"at":[148],"<uri":[149],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[150],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/njusthyk1972/NLH</uri>":[151],".":[152]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":4}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2019-06-27T00:00:00"}
