{"id":"https://openalex.org/W2151614069","doi":"https://doi.org/10.1109/lsp.2014.2337274","title":"A Higher-Order MRF Based Variational Model for Multiplicative Noise Reduction","display_name":"A Higher-Order MRF Based Variational Model for Multiplicative Noise Reduction","publication_year":2014,"publication_date":"2014-07-09","ids":{"openalex":"https://openalex.org/W2151614069","doi":"https://doi.org/10.1109/lsp.2014.2337274","mag":"2151614069"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2014.2337274","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2014.2337274","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1404.5344","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yunjin Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Yunjin Chen","raw_affiliation_strings":["Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria","institution_ids":["https://openalex.org/I4092182"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wensen Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wensen Feng","raw_affiliation_strings":["University of Science and Technology Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Rene Ranftl","orcid":null},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Rene Ranftl","raw_affiliation_strings":["Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria","institution_ids":["https://openalex.org/I4092182"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hong Qiao","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Qiao","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Automation, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Automation, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"last","author":{"id":null,"display_name":"Thomas Pock","orcid":null},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Thomas Pock","raw_affiliation_strings":["Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria","institution_ids":["https://openalex.org/I4092182"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.4769,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.93394114,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"21","issue":"11","first_page":"1370","last_page":"1374"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9032999873161316,"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":0.9032999873161316,"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":0.033799998462200165,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.01679999940097332,"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/multiplicative-noise","display_name":"Multiplicative noise","score":0.6762999892234802},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6635000109672546},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.5792999863624573},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5648000240325928},{"id":"https://openalex.org/keywords/multiplicative-function","display_name":"Multiplicative function","score":0.5483999848365784},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5403000116348267},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.5206999778747559},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.4902999997138977},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46720001101493835},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4643999934196472}],"concepts":[{"id":"https://openalex.org/C18015164","wikidata":"https://www.wikidata.org/wiki/Q6935000","display_name":"Multiplicative noise","level":5,"score":0.6762999892234802},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6635000109672546},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.5792999863624573},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5648000240325928},{"id":"https://openalex.org/C42747912","wikidata":"https://www.wikidata.org/wiki/Q1048447","display_name":"Multiplicative function","level":2,"score":0.5483999848365784},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5403000116348267},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.5206999778747559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5098999738693237},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4977000057697296},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.4902999997138977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47029998898506165},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46720001101493835},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4643999934196472},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.45910000801086426},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.4496000111103058},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3917999863624573},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3894999921321869},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.38269999623298645},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3723999857902527},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.3619999885559082},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.35499998927116394},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.3422999978065491},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3377000093460083},{"id":"https://openalex.org/C2986577269","wikidata":"https://www.wikidata.org/wiki/Q11306265","display_name":"Random noise","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.3057999908924103},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.28529998660087585},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.28220000863075256},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26820001006126404},{"id":"https://openalex.org/C109094680","wikidata":"https://www.wikidata.org/wiki/Q6060432","display_name":"Inverse synthetic aperture radar","level":4,"score":0.2632000148296356},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.26269999146461487},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2014.2337274","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2014.2337274","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1404.5344","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1404.5344","pdf_url":"https://arxiv.org/pdf/1404.5344","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:1404.5344","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1404.5344","pdf_url":"https://arxiv.org/pdf/1404.5344","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":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1970478368","https://openalex.org/W1976747969","https://openalex.org/W1998339281","https://openalex.org/W2000462146","https://openalex.org/W2000594266","https://openalex.org/W2004376198","https://openalex.org/W2010825468","https://openalex.org/W2022459032","https://openalex.org/W2049893860","https://openalex.org/W2056370875","https://openalex.org/W2068728923","https://openalex.org/W2104763670","https://openalex.org/W2130184048","https://openalex.org/W2133665775","https://openalex.org/W2142344058","https://openalex.org/W2144851790","https://openalex.org/W2155969596","https://openalex.org/W2162457349","https://openalex.org/W2164611927","https://openalex.org/W2165045991","https://openalex.org/W6638840822"],"related_works":[],"abstract_inverted_index":{"The":[0,54],"Fields":[1,13],"of":[2,31,93],"Experts":[3],"(FoE)":[4],"image":[5,24,51],"prior":[6,52],"model,":[7,15],"a":[8,39,59,69],"filter-based":[9],"higher-order":[10],"Markov":[11],"Random":[12],"(MRF)":[14],"has":[16],"been":[17],"shown":[18],"to":[19,58,130],"be":[20,65],"effective":[21],"for":[22,43],"many":[23],"restoration":[25],"problems.":[26],"Motivated":[27],"by":[28,68],"the":[29,49,91,101,117],"successes":[30],"FoE-based":[32],"approaches,":[33],"in":[34],"this":[35],"letter":[36],"we":[37],"propose":[38],"novel":[40],"variational":[41],"model":[42,56,109],"multiplicative":[44],"noise":[45,81],"reduction":[46],"based":[47,77,124],"on":[48,78,98],"FoE":[50],"model.":[53],"resulting":[55],"corresponds":[57],"non-convex":[60,72],"minimization":[61],"problem,":[62],"which":[63],"can":[64],"efficiently":[66],"solved":[67],"recently":[70],"published":[71,103],"optimization":[73],"algorithm.":[74,105],"Experimental":[75],"results":[76],"synthetic":[79,84],"speckle":[80],"and":[82],"real":[83],"aperture":[85],"radar":[86],"(SAR)":[87],"images":[88],"suggest":[89],"that":[90,116],"performance":[92],"our":[94,107],"proposed":[95,108],"method":[96],"is":[97,119],"par":[99],"with":[100,112],"best":[102],"despeckling":[104,133],"Besides,":[106],"comes":[110],"along":[111],"an":[113],"additional":[114],"advantage,":[115],"inference":[118],"extremely":[120],"efficient.":[121],"Our":[122],"GPU":[123],"implementation":[125],"takes":[126],"less":[127],"than":[128],"1s":[129],"produce":[131],"state-of-the-art":[132],"performance.":[134]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2016-06-24T00:00:00"}
