{"id":"https://openalex.org/W2945392724","doi":"https://doi.org/10.1137/18m1187192","title":"Multiplicative Noise Removal for Texture Images Based on Adaptive Anisotropic Fractional Diffusion Equations","display_name":"Multiplicative Noise Removal for Texture Images Based on Adaptive Anisotropic Fractional Diffusion Equations","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2945392724","doi":"https://doi.org/10.1137/18m1187192","mag":"2945392724"},"language":"en","primary_location":{"id":"doi:10.1137/18m1187192","is_oa":false,"landing_page_url":"https://doi.org/10.1137/18m1187192","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","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/A5049938916","display_name":"Wenjuan Yao","orcid":"https://orcid.org/0000-0001-9463-9507"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wenjuan Yao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001168822","display_name":"Zhichang Guo","orcid":"https://orcid.org/0009-0007-3804-4980"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhichang Guo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101680536","display_name":"Jiebao Sun","orcid":"https://orcid.org/0000-0003-3511-2873"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiebao Sun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061700722","display_name":"Boying Wu","orcid":"https://orcid.org/0000-0002-5611-650X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boying Wu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5036684787","display_name":"Huijun Gao","orcid":"https://orcid.org/0000-0001-5554-5452"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huijun Gao","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5049938916"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2269,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":{"value":0.9052951,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"12","issue":"2","first_page":"839","last_page":"873"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9997000098228455,"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":0.9997000098228455,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9908999800682068,"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/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.9886999726295471,"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/multiplicative-noise","display_name":"Multiplicative noise","score":0.8134253025054932},{"id":"https://openalex.org/keywords/anisotropic-diffusion","display_name":"Anisotropic diffusion","score":0.6881263256072998},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5880932807922363},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5842171907424927},{"id":"https://openalex.org/keywords/gradient-noise","display_name":"Gradient noise","score":0.5378093123435974},{"id":"https://openalex.org/keywords/value-noise","display_name":"Value noise","score":0.5230958461761475},{"id":"https://openalex.org/keywords/multiplicative-function","display_name":"Multiplicative function","score":0.5197855830192566},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5088379979133606},{"id":"https://openalex.org/keywords/fractional-calculus","display_name":"Fractional calculus","score":0.45980894565582275},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35613784193992615},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3460136950016022},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.32862433791160583},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30696389079093933},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.2892381548881531},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.237675279378891},{"id":"https://openalex.org/keywords/median-filter","display_name":"Median filter","score":0.22172042727470398}],"concepts":[{"id":"https://openalex.org/C18015164","wikidata":"https://www.wikidata.org/wiki/Q6935000","display_name":"Multiplicative noise","level":5,"score":0.8134253025054932},{"id":"https://openalex.org/C203504353","wikidata":"https://www.wikidata.org/wiki/Q4765461","display_name":"Anisotropic diffusion","level":3,"score":0.6881263256072998},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5880932807922363},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5842171907424927},{"id":"https://openalex.org/C200378446","wikidata":"https://www.wikidata.org/wiki/Q4147391","display_name":"Gradient noise","level":5,"score":0.5378093123435974},{"id":"https://openalex.org/C182163834","wikidata":"https://www.wikidata.org/wiki/Q2926529","display_name":"Value noise","level":5,"score":0.5230958461761475},{"id":"https://openalex.org/C42747912","wikidata":"https://www.wikidata.org/wiki/Q1048447","display_name":"Multiplicative function","level":2,"score":0.5197855830192566},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5088379979133606},{"id":"https://openalex.org/C154249771","wikidata":"https://www.wikidata.org/wiki/Q1339058","display_name":"Fractional calculus","level":2,"score":0.45980894565582275},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35613784193992615},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3460136950016022},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.32862433791160583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30696389079093933},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2892381548881531},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.237675279378891},{"id":"https://openalex.org/C55352655","wikidata":"https://www.wikidata.org/wiki/Q304247","display_name":"Median filter","level":4,"score":0.22172042727470398},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0},{"id":"https://openalex.org/C131021393","wikidata":"https://www.wikidata.org/wiki/Q7512759","display_name":"Signal transfer function","level":4,"score":0.0},{"id":"https://openalex.org/C13412647","wikidata":"https://www.wikidata.org/wiki/Q174948","display_name":"Analog signal","level":3,"score":0.0},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/18m1187192","is_oa":false,"landing_page_url":"https://doi.org/10.1137/18m1187192","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4295320098","display_name":null,"funder_award_id":"51476047","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4851906098","display_name":null,"funder_award_id":"201601","funder_id":"https://openalex.org/F4320321940","funder_display_name":"Harbin Institute of Technology"},{"id":"https://openalex.org/G5016088536","display_name":null,"funder_award_id":"A2016003","funder_id":"https://openalex.org/F4320323085","funder_display_name":"Natural Science Foundation of Heilongjiang Province"},{"id":"https://openalex.org/G732353624","display_name":null,"funder_award_id":"11271100","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8972181338","display_name":null,"funder_award_id":"201609","funder_id":"https://openalex.org/F4320321940","funder_display_name":"Harbin Institute of Technology"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321940","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08"},{"id":"https://openalex.org/F4320323085","display_name":"Natural Science Foundation of Heilongjiang Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1516198666","https://openalex.org/W1601669748","https://openalex.org/W1606169230","https://openalex.org/W1977700559","https://openalex.org/W1985507365","https://openalex.org/W1991217933","https://openalex.org/W1998339281","https://openalex.org/W2002912860","https://openalex.org/W2004376198","https://openalex.org/W2004928853","https://openalex.org/W2006786206","https://openalex.org/W2011516671","https://openalex.org/W2013388817","https://openalex.org/W2014311222","https://openalex.org/W2020461703","https://openalex.org/W2021537669","https://openalex.org/W2022735534","https://openalex.org/W2027051720","https://openalex.org/W2031753087","https://openalex.org/W2036266090","https://openalex.org/W2036756869","https://openalex.org/W2037981501","https://openalex.org/W2038882741","https://openalex.org/W2039612688","https://openalex.org/W2048322459","https://openalex.org/W2052086239","https://openalex.org/W2060945009","https://openalex.org/W2061800457","https://openalex.org/W2065267700","https://openalex.org/W2073935280","https://openalex.org/W2074319623","https://openalex.org/W2077282160","https://openalex.org/W2093014173","https://openalex.org/W2094634730","https://openalex.org/W2099914796","https://openalex.org/W2107162131","https://openalex.org/W2108179490","https://openalex.org/W2108710836","https://openalex.org/W2111899019","https://openalex.org/W2114898750","https://openalex.org/W2122287830","https://openalex.org/W2130094715","https://openalex.org/W2132236849","https://openalex.org/W2133665775","https://openalex.org/W2140207570","https://openalex.org/W2148791483","https://openalex.org/W2150134853","https://openalex.org/W2161811007","https://openalex.org/W2171857449","https://openalex.org/W2250496345","https://openalex.org/W2268440417","https://openalex.org/W2518477744","https://openalex.org/W2527620157","https://openalex.org/W2548712274","https://openalex.org/W2604292070","https://openalex.org/W2963101071"],"related_works":["https://openalex.org/W2056920477","https://openalex.org/W2949211747","https://openalex.org/W2085803788","https://openalex.org/W4378464573","https://openalex.org/W2391941905","https://openalex.org/W2394041740","https://openalex.org/W2299604426","https://openalex.org/W2884752167","https://openalex.org/W2541083084","https://openalex.org/W1652574860"],"abstract_inverted_index":{"Multiplicative":[0],"noise":[1,13,17,61,154],"removal":[2,14,155],"problems":[3],"have":[4],"attracted":[5],"much":[6],"attention":[7],"in":[8,84,91],"recent":[9],"years.":[10],"Unlike":[11],"additive":[12,113],"problems,":[15],"multiplicative":[16,47,60,153],"destroys":[18],"almost":[19],"all":[20],"information":[21],"of":[22,71,101,127,140],"the":[23,42,50,72,76,85,92,99,102,108,123,128,136,141,148],"original":[24],"image,":[25],"especially":[26],"for":[27,66,112],"texture":[28,43,67,157],"images.":[29,68],"In":[30,49],"this":[31],"paper,":[32],"a":[33,52,117],"fractional-order":[34,104],"nonlinear":[35],"diffusion":[36],"model":[37,77,150],"is":[38,56,78,95],"proposed":[39,142,149],"to":[40,58,134],"denoise":[41],"images":[44],"corrupted":[45],"by":[46,80,107],"noise.":[48,129],"model,":[51],"gray":[53],"level":[54],"indicator":[55],"introduced":[57],"remove":[59],"and":[62,125,138,156],"preserve":[63],"structure":[64],"details":[65],"By":[69],"virtue":[70],"discrete":[73],"Fourier":[74],"transform,":[75],"solved":[79],"an":[81,89],"iterative":[82],"scheme":[83],"frequency":[86],"domain.":[87],"Then":[88],"algorithm":[90],"spatial":[93],"domain":[94],"developed":[96],"based":[97,121],"on":[98,122],"definition":[100],"Gr\u00fcnwald--Letnikov":[103],"derivative.":[105],"Inspired":[106],"discrepancy":[109],"principle":[110],"used":[111],"noise,":[114],"we":[115],"develop":[116],"new":[118],"stopping":[119],"criterion":[120],"mean":[124],"variance":[126],"Numerical":[130],"examples":[131],"are":[132],"presented":[133],"demonstrate":[135],"effectiveness":[137],"efficiency":[139],"method.":[143],"Experimental":[144],"results":[145],"show":[146],"that":[147],"can":[151],"handle":[152],"preservation":[158],"quite":[159],"well.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
