{"id":"https://openalex.org/W2163204144","doi":"https://doi.org/10.1109/tip.2008.2011388","title":"Passive Error Concealment for Wavelet-Coded I-Frames With an Inhomogeneous Gauss\u2013Markov Random Field Model","display_name":"Passive Error Concealment for Wavelet-Coded I-Frames With an Inhomogeneous Gauss\u2013Markov Random Field Model","publication_year":2009,"publication_date":"2009-02-26","ids":{"openalex":"https://openalex.org/W2163204144","doi":"https://doi.org/10.1109/tip.2008.2011388","mag":"2163204144","pmid":"https://pubmed.ncbi.nlm.nih.gov/19244021"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2008.2011388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2008.2011388","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/A5059570724","display_name":"Joost Rombaut","orcid":null},"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":"J. Rombaut","raw_affiliation_strings":["Department for Telecommunications and Information Processing, Ghent University, Sint-Pietersnieuwstraat 41, Ghent, Belgium. joost.rombaut@telin.ugent.be","Department of Telecommunications and Information Processing (UGent-TELIN-IPI-IBBT), Ghent University, Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"Department for Telecommunications and Information Processing, Ghent University, Sint-Pietersnieuwstraat 41, Ghent, Belgium. joost.rombaut@telin.ugent.be","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"Department of Telecommunications and Information Processing (UGent-TELIN-IPI-IBBT), Ghent University, 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/I2802067006","display_name":"Research Foundation - Flanders","ror":"https://ror.org/03qtxy027","country_code":"BE","type":"government","lineage":["https://openalex.org/I2802067006"]},{"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 (UGent-TELIN-IPI-IBBT), Ghent University, Ghent, Belgium","FWO, Flanders, Belgium"],"affiliations":[{"raw_affiliation_string":"Department of Telecommunications and Information Processing (UGent-TELIN-IPI-IBBT), Ghent University, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"FWO, Flanders, Belgium","institution_ids":["https://openalex.org/I2802067006"]}]},{"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 (UGent-TELIN-IPI-IBBT), Ghent University, Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"Department of Telecommunications and Information Processing (UGent-TELIN-IPI-IBBT), Ghent University, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059570724"],"corresponding_institution_ids":["https://openalex.org/I32597200"],"apc_list":null,"apc_paid":null,"fwci":1.2943,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.83656718,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"18","issue":"4","first_page":"783","last_page":"796"},"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/T10901","display_name":"Advanced Data Compression Techniques","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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9983000159263611,"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/computer-science","display_name":"Computer science","score":0.6348146200180054},{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.6242595314979553},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5773978233337402},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.554520845413208},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5132718086242676},{"id":"https://openalex.org/keywords/random-field","display_name":"Random field","score":0.48908334970474243},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4831933081150055},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4619351625442505},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4502142071723938},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.4458683431148529},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.4327201843261719},{"id":"https://openalex.org/keywords/error-detection-and-correction","display_name":"Error detection and correction","score":0.41926732659339905},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.41450557112693787},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4115253686904907},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3676673173904419},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3628457486629486},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2900487780570984},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15888765454292297},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12311497330665588},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.09796899557113647}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6348146200180054},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.6242595314979553},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5773978233337402},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.554520845413208},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5132718086242676},{"id":"https://openalex.org/C130402806","wikidata":"https://www.wikidata.org/wiki/Q5361768","display_name":"Random field","level":2,"score":0.48908334970474243},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4831933081150055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4619351625442505},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4502142071723938},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.4458683431148529},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.4327201843261719},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.41926732659339905},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.41450557112693787},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4115253686904907},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3676673173904419},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3628457486629486},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2900487780570984},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15888765454292297},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12311497330665588},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.09796899557113647},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2008.2011388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2008.2011388","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:19244021","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/19244021","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:archive.ugent.be:539089","is_oa":false,"landing_page_url":"http://hdl.handle.net/1854/LU-539089","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":[{"score":0.5799999833106995,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W18046889","https://openalex.org/W1507028917","https://openalex.org/W1598760490","https://openalex.org/W1989222601","https://openalex.org/W1997027115","https://openalex.org/W1998172750","https://openalex.org/W2006804812","https://openalex.org/W2013678917","https://openalex.org/W2020999234","https://openalex.org/W2046033161","https://openalex.org/W2049824313","https://openalex.org/W2053691921","https://openalex.org/W2057612871","https://openalex.org/W2062024414","https://openalex.org/W2065301447","https://openalex.org/W2073385196","https://openalex.org/W2098507775","https://openalex.org/W2100563391","https://openalex.org/W2101789093","https://openalex.org/W2102373785","https://openalex.org/W2106200738","https://openalex.org/W2106481715","https://openalex.org/W2108081708","https://openalex.org/W2114220616","https://openalex.org/W2115755118","https://openalex.org/W2119945597","https://openalex.org/W2121351349","https://openalex.org/W2126397022","https://openalex.org/W2132984323","https://openalex.org/W2135788072","https://openalex.org/W2136910298","https://openalex.org/W2142994166","https://openalex.org/W2152779123","https://openalex.org/W2153703004","https://openalex.org/W2162587881","https://openalex.org/W2166168490","https://openalex.org/W2169327696","https://openalex.org/W2725842440","https://openalex.org/W3179299791","https://openalex.org/W4255272544","https://openalex.org/W6798352906"],"related_works":["https://openalex.org/W2156342195","https://openalex.org/W987019958","https://openalex.org/W2030382593","https://openalex.org/W1983122994","https://openalex.org/W2078379274","https://openalex.org/W4233015508","https://openalex.org/W2099971354","https://openalex.org/W2133071149","https://openalex.org/W2101965184","https://openalex.org/W2574864235"],"abstract_inverted_index":{"In":[0],"video":[1,21],"communication":[2],"over":[3,123],"lossy":[4],"packet":[5,10],"networks":[6],"(e.g.,":[7],"the":[8,16,41,67,97,113,124,141,146,149,152],"Internet),":[9],"loss":[11],"errors":[12],"can":[13,22],"severely":[14],"damage":[15],"transmitted":[17],"video.":[18],"The":[19,54,117,137],"damaged":[20],"largely":[23],"be":[24],"repaired":[25],"with":[26,51],"passive":[27,44],"error":[28,45,79],"concealment,":[29],"where":[30],"neighboring":[31],"information":[32,157],"is":[33,151],"used":[34],"to":[35,145],"estimate":[36,96],"missing":[37],"information.":[38],"We":[39,95],"address":[40],"problem":[42],"of":[43,57,69,99,106,131,140,155],"concealment":[46,80],"for":[47,82],"wavelet":[48],"coded":[49,84],"data":[50],"dispersive":[52],"packetization.":[53],"reported":[55,125],"techniques":[56],"this":[58,100],"kind":[59],"have":[60],"many":[61],"problems":[62],"and":[63,110,135,161],"usually":[64],"fail":[65],"in":[66,129,148],"reconstruction":[68,154],"high-frequency":[70,156],"content.":[71],"This":[72],"paper":[73],"presents":[74],"a":[75,103,120],"novel":[76],"locally":[77],"adaptive":[78],"method":[81,143],"subband":[83],"I-frames":[85],"based":[86],"on":[87],"an":[88],"inhomogeneous":[89],"Gaussian":[90],"Markov":[91],"random":[92],"field":[93,150],"model.":[94],"parameters":[98],"model":[101],"from":[102],"local":[104],"context":[105],"each":[107],"lost":[108,114],"coefficient,":[109],"we":[111],"interpolate":[112],"coefficients":[115],"accordingly.":[116],"results":[118],"demonstrate":[119],"significant":[121],"improvement":[122,139],"related":[126],"methods":[127],"both":[128],"terms":[130],"objective":[132],"performance":[133],"measures":[134],"visually.":[136],"biggest":[138],"proposed":[142],"compared":[144],"state-of-the-art":[147],"correct":[153],"such":[158],"as":[159],"textures":[160],"edges.":[162]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}