{"id":"https://openalex.org/W2040675601","doi":"https://doi.org/10.1109/tip.2009.2022006","title":"Image Denoising Using Mixtures of Projected Gaussian Scale Mixtures","display_name":"Image Denoising Using Mixtures of Projected Gaussian Scale Mixtures","publication_year":2009,"publication_date":"2009-05-04","ids":{"openalex":"https://openalex.org/W2040675601","doi":"https://doi.org/10.1109/tip.2009.2022006","mag":"2040675601","pmid":"https://pubmed.ncbi.nlm.nih.gov/19414286"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2009.2022006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2009.2022006","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":["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/A5085936068","display_name":"Bart Goossens","orcid":"https://orcid.org/0000-0002-1666-5483"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"B. Goossens","raw_affiliation_strings":["Department of Telecommunications and Information Processing (TELIN-IPI-IBBT), Ghent University, B-9000 Gent, Belgium. bart.goossens@telin.ugent.be","Dept. of Telecommun. & Inf. Process. (TELIN-IPI-IBBT), Ghent Univ., Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"Department of Telecommunications and Information Processing (TELIN-IPI-IBBT), Ghent University, B-9000 Gent, Belgium. bart.goossens@telin.ugent.be","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"Dept. of Telecommun. & Inf. Process. (TELIN-IPI-IBBT), Ghent Univ., Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031078128","display_name":"Aleksandra Pi\u017eurica","orcid":"https://orcid.org/0000-0002-9322-4999"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"A. Pizurica","raw_affiliation_strings":["Department of Telecommunications and Information Processing TELIN IPI IBBT, Ghent University, Ghent, Belgium","Dept. of Telecommun. & Inf. Process. (TELIN-IPI-IBBT), Ghent Univ., Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"Department of Telecommunications and Information Processing TELIN IPI IBBT, Ghent University, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"Dept. of Telecommun. & Inf. Process. (TELIN-IPI-IBBT), Ghent Univ., Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071483672","display_name":"Wilfried Philips","orcid":"https://orcid.org/0000-0003-4456-4353"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"W. Philips","raw_affiliation_strings":["Department of Telecommunications and Information Processing TELIN IPI IBBT, Ghent University, Ghent, Belgium","Dept. of Telecommun. & Inf. Process. (TELIN-IPI-IBBT), Ghent Univ., Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"Department of Telecommunications and Information Processing TELIN IPI IBBT, Ghent University, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"Dept. of Telecommun. & Inf. Process. (TELIN-IPI-IBBT), Ghent Univ., Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5085936068"],"corresponding_institution_ids":["https://openalex.org/I32597200"],"apc_list":null,"apc_paid":null,"fwci":3.9367,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.94108405,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"18","issue":"8","first_page":"1689","last_page":"1702"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9907000064849854,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.987500011920929,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.623532235622406},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5838198661804199},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5726287364959717},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5163716077804565},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5147666931152344},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4812983572483063},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4765082895755768},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4715157747268677},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46967893838882446},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4456167221069336},{"id":"https://openalex.org/keywords/non-local-means","display_name":"Non-local means","score":0.44499388337135315},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.4304807186126709},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4262838065624237},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4046935439109802},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.26172101497650146}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.623532235622406},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5838198661804199},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5726287364959717},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5163716077804565},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5147666931152344},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4812983572483063},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4765082895755768},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4715157747268677},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46967893838882446},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4456167221069336},{"id":"https://openalex.org/C101453961","wikidata":"https://www.wikidata.org/wiki/Q7048948","display_name":"Non-local means","level":4,"score":0.44499388337135315},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.4304807186126709},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4262838065624237},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4046935439109802},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.26172101497650146},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tip.2009.2022006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2009.2022006","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":"pmid:19414286","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/19414286","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.331.1084","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.331.1084","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://telin.ugent.be/~sanja/Papers/MPGSM.pdf","raw_type":"text"},{"id":"pmh:oai:archive.ugent.be:1002612","is_oa":false,"landing_page_url":"https://biblio.ugent.be/publication/1002612","pdf_url":null,"source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN: 1057-7149","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.75,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1488588536","https://openalex.org/W1536252645","https://openalex.org/W1570876803","https://openalex.org/W1978355185","https://openalex.org/W2001141328","https://openalex.org/W2003726505","https://openalex.org/W2049633694","https://openalex.org/W2053186076","https://openalex.org/W2053691921","https://openalex.org/W2056370875","https://openalex.org/W2060542838","https://openalex.org/W2062373208","https://openalex.org/W2065391104","https://openalex.org/W2071128523","https://openalex.org/W2098415878","https://openalex.org/W2100247253","https://openalex.org/W2106004362","https://openalex.org/W2107216283","https://openalex.org/W2108456818","https://openalex.org/W2109812093","https://openalex.org/W2113945798","https://openalex.org/W2119548491","https://openalex.org/W2122714239","https://openalex.org/W2124812588","https://openalex.org/W2129276048","https://openalex.org/W2134929491","https://openalex.org/W2136910298","https://openalex.org/W2140136927","https://openalex.org/W2140667604","https://openalex.org/W2142561145","https://openalex.org/W2144451417","https://openalex.org/W2146610201","https://openalex.org/W2146842127","https://openalex.org/W2148694408","https://openalex.org/W2151035455","https://openalex.org/W2152047336","https://openalex.org/W2152652402","https://openalex.org/W2153168413","https://openalex.org/W2153663612","https://openalex.org/W2158162781","https://openalex.org/W2163612361","https://openalex.org/W2165918462","https://openalex.org/W2166054752","https://openalex.org/W2166982406","https://openalex.org/W2167034998","https://openalex.org/W2169100314","https://openalex.org/W2171739832","https://openalex.org/W2567948266","https://openalex.org/W3015571647","https://openalex.org/W4238805501","https://openalex.org/W4289257589","https://openalex.org/W4292023222","https://openalex.org/W6682789403"],"related_works":["https://openalex.org/W2541950815","https://openalex.org/W4210725687","https://openalex.org/W2058614856","https://openalex.org/W1577789985","https://openalex.org/W2037328875","https://openalex.org/W1982375519","https://openalex.org/W2942471066","https://openalex.org/W2349049920","https://openalex.org/W2128714091","https://openalex.org/W1980997268"],"abstract_inverted_index":{"We":[0,94],"propose":[1],"a":[2,18,31,52,65,96,119,127,149],"new":[3],"statistical":[4],"model":[5,50],"for":[6,91],"image":[7],"restoration":[8],"in":[9,46,69,156],"which":[10,87],"neighborhoods":[11],"of":[12,21,35,54,59,103,130,145],"wavelet":[13,78],"subbands":[14],"are":[15],"modeled":[16],"by":[17],"discrete":[19],"mixture":[20],"linear":[22],"projected":[23],"Gaussian":[24],"Scale":[25],"Mixtures":[26],"(MPGSM).":[27],"In":[28],"each":[29],"projection,":[30],"lower":[32],"dimensional":[33],"approximation":[34],"the":[36,43,55,75,81,104,110,138,160],"local":[37],"neighborhood":[38],"is":[39,51,84],"obtained,":[40],"thereby":[41],"modeling":[42],"strongest":[44],"correlations":[45],"that":[47,63,100],"neighborhood.":[48],"The":[49,112],"generalization":[53],"recently":[56],"developed":[57],"Mixture":[58],"GSM":[60],"(MGSM)":[61],"model,":[62],"offers":[64],"significant":[66],"improvement":[67],"both":[68,153],"PSNR":[70,131,157],"and":[71,155],"visually":[72,154],"compared":[73,158],"to":[74,107,137,159],"current":[76,161],"state-of-the-art":[77,163],"techniques.":[79],"However,":[80],"computation":[82],"cost":[83],"very":[85],"high":[86],"hampers":[88],"its":[89],"use":[90],"practical":[92],"purposes.":[93],"present":[95],"fast":[97],"EM":[98],"algorithm":[99],"takes":[101],"advantage":[102],"projection":[105],"bases":[106,144],"speed":[108],"up":[109],"algorithm.":[111],"results":[113],"show":[114],"that,":[115],"when":[116],"projecting":[117],"on":[118],"fixed":[120],"data-independent":[121],"basis,":[122],"even":[123],"computational":[124],"advantages":[125],"with":[126,135],"limited":[128],"loss":[129],"can":[132],"be":[133],"obtained":[134],"respect":[136],"BLS-GSM":[139],"denoising":[140,151,164],"method,":[141],"while":[142],"data-dependent":[143],"Principle":[146],"Components":[147],"offer":[148],"higher":[150],"performance,":[152],"wavelet-based":[162],"methods.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":5}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}