{"id":"https://openalex.org/W2690801559","doi":"https://doi.org/10.1109/tcyb.2017.2713421","title":"Fast and Accurate Poisson Denoising With Trainable Nonlinear Diffusion","display_name":"Fast and Accurate Poisson Denoising With Trainable Nonlinear Diffusion","publication_year":2017,"publication_date":"2017-06-20","ids":{"openalex":"https://openalex.org/W2690801559","doi":"https://doi.org/10.1109/tcyb.2017.2713421","mag":"2690801559","pmid":"https://pubmed.ncbi.nlm.nih.gov/28644816"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2017.2713421","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2017.2713421","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5084330706","display_name":"Wensen Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wensen Feng","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058476148","display_name":"Peng Qiao","orcid":"https://orcid.org/0000-0001-6752-7892"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Qiao","raw_affiliation_strings":["National Laboratory for Parallel and Distributed Processing, School of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory for Parallel and Distributed Processing, School of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077938164","display_name":"Yunjin Chen","orcid":"https://orcid.org/0000-0002-4428-2797"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yunjin Chen","raw_affiliation_strings":["ULSee Inc., Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"ULSee Inc., Hangzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084330706"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":1.0923,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.86113745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"48","issue":"6","first_page":"1708","last_page":"1719"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987000226974487,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/noise-reduction","display_name":"Noise reduction","score":0.7264754772186279},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6803003549575806},{"id":"https://openalex.org/keywords/shot-noise","display_name":"Shot noise","score":0.5875373482704163},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5304020643234253},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5126773118972778},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.5105646848678589},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5011720657348633},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.4680810868740082},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.452565461397171},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.45223918557167053},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.44996777176856995},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.44982072710990906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3575015962123871},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.27631106972694397},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24264368414878845},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2118537724018097},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1081261932849884},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0823260247707367}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.7264754772186279},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6803003549575806},{"id":"https://openalex.org/C72659945","wikidata":"https://www.wikidata.org/wiki/Q1503574","display_name":"Shot noise","level":3,"score":0.5875373482704163},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5304020643234253},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5126773118972778},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.5105646848678589},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5011720657348633},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.4680810868740082},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.452565461397171},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.45223918557167053},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.44996777176856995},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.44982072710990906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3575015962123871},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27631106972694397},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24264368414878845},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2118537724018097},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1081261932849884},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0823260247707367},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2017.2713421","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2017.2713421","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","raw_type":"journal-article"},{"id":"pmid:28644816","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28644816","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on cybernetics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6800000071525574}],"awards":[{"id":"https://openalex.org/G5075636046","display_name":null,"funder_award_id":"61602032","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W755141289","https://openalex.org/W1609373452","https://openalex.org/W1915360731","https://openalex.org/W1971066121","https://openalex.org/W1987057208","https://openalex.org/W1993032016","https://openalex.org/W2021262032","https://openalex.org/W2024829682","https://openalex.org/W2028348398","https://openalex.org/W2050892949","https://openalex.org/W2051434435","https://openalex.org/W2056370875","https://openalex.org/W2069441534","https://openalex.org/W2071005004","https://openalex.org/W2072761496","https://openalex.org/W2083799719","https://openalex.org/W2098477387","https://openalex.org/W2108335642","https://openalex.org/W2110264793","https://openalex.org/W2110652930","https://openalex.org/W2112796928","https://openalex.org/W2121927366","https://openalex.org/W2122512929","https://openalex.org/W2124541940","https://openalex.org/W2127324070","https://openalex.org/W2128058389","https://openalex.org/W2130184048","https://openalex.org/W2133665775","https://openalex.org/W2135001774","https://openalex.org/W2138461515","https://openalex.org/W2145876651","https://openalex.org/W2148791483","https://openalex.org/W2155969596","https://openalex.org/W2170942820","https://openalex.org/W2298855392","https://openalex.org/W2397583963","https://openalex.org/W2568381517","https://openalex.org/W3101833857","https://openalex.org/W3106237033","https://openalex.org/W4250507776","https://openalex.org/W6657624138","https://openalex.org/W6674855086"],"related_works":["https://openalex.org/W4206903459","https://openalex.org/W2754816816","https://openalex.org/W4366280654","https://openalex.org/W3160167280","https://openalex.org/W4231621013","https://openalex.org/W4362706668","https://openalex.org/W3008318776","https://openalex.org/W1977633006","https://openalex.org/W1971945429","https://openalex.org/W2041416246"],"abstract_inverted_index":{"The":[0,159],"degradation":[1],"of":[2,173,205],"the":[3,43,72,96,103,121,128,132,142,171,190],"acquired":[4],"signal":[5],"by":[6,138],"Poisson":[7,30,56,143,157,219],"noise":[8,144],"is":[9,108,193],"a":[10,150],"common":[11],"problem":[12],"for":[13,42,156,195],"various":[14],"imaging":[15],"applications,":[16],"such":[17],"as":[18],"medical":[19],"imaging,":[20],"night":[21],"vision,":[22],"and":[23,64,135,146,176],"microscopy.":[24],"Up":[25],"to":[26,52,120,216],"now,":[27],"many":[28],"state-of-the-art":[29,167,218],"denoising":[31,57,106,220],"techniques":[32],"mainly":[33],"concentrate":[34],"on":[35,198],"achieving":[36],"utmost":[37],"performance,":[38],"with":[39,59,90,149,185],"little":[40],"consideration":[41],"computation":[44,197],"efficiency.":[45,178],"Therefore,":[46],"in":[47,102,111],"this":[48,68,112,116],"paper":[49],"we":[50,70,118],"aim":[51],"propose":[53],"an":[54,84,186],"efficient":[55],"model":[58,80,129,154,161,182],"both":[60],"high":[61,177],"computational":[62],"efficiency":[63],"recovery":[65],"quality.":[66],"To":[67,114],"end,":[69],"exploit":[71],"newly":[73],"developed":[74],"trainable":[75],"nonlinear":[76,152],"reaction":[77],"diffusion":[78,153,191],"(TNRD)":[79],"which":[81],"has":[82],"proven":[83],"extremely":[85],"fast":[86],"image":[87],"restoration":[88],"approach":[89],"performance":[91],"surpassing":[92],"recent":[93],"state-of-the-arts.":[94],"However,":[95],"straightforward":[97],"direct":[98],"gradient":[99,123],"descent":[100,124],"employed":[101],"original":[104],"TNRD-based":[105],"task":[107],"not":[109],"applicable":[110],"paper.":[113],"solve":[115],"problem,":[117],"resort":[119],"proximal":[122],"method.":[125],"We":[126],"retrain":[127],"parameters,":[130],"including":[131],"linear":[133],"filters":[134],"influence":[136],"functions":[137],"taking":[139],"into":[140],"account":[141],"statistics,":[145],"end":[147],"up":[148],"well-trained":[151],"specialized":[155],"denoising.":[158],"trained":[160],"provides":[162],"strongly":[163],"competitive":[164],"results":[165],"against":[166],"approaches,":[168],"meanwhile":[169],"bearing":[170],"properties":[172],"simple":[174],"structure":[175],"Furthermore,":[179],"our":[180,208],"proposed":[181],"comes":[183],"along":[184],"additional":[187],"advantage,":[188],"that":[189],"process":[192],"well-suited":[194],"parallel":[196],"graphics":[199],"processing":[200],"units":[201],"(GPUs).":[202],"For":[203],"images":[204],"size":[206],",":[207],"GPU":[209],"implementation":[210],"takes":[211],"less":[212],"than":[213],"0.1":[214],"s":[215],"produce":[217],"performance.":[221]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
