{"id":"https://openalex.org/W6907493344","doi":"https://doi.org/10.2312/egmm/mm04/105-113","title":"A Training-Based Method for Reducing Ringing Artifact in BDCT-Encoded Images","display_name":"A Training-Based Method for Reducing Ringing Artifact in BDCT-Encoded Images","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W6907493344","doi":"https://doi.org/10.2312/egmm/mm04/105-113"},"language":"en","primary_location":{"id":"doi:10.2312/egmm/mm04/105-113","is_oa":true,"landing_page_url":"https://doi.org/10.2312/egmm/mm04/105-113","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"other","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.2312/egmm/mm04/105-113","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Wang, Guangyu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wang, Guangyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Wong, Tien-Tsin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wong, Tien-Tsin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Heng, Pheng-Ann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heng, Pheng-Ann","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.7750999927520752},{"id":"https://openalex.org/keywords/ringing","display_name":"Ringing","score":0.7724000215530396},{"id":"https://openalex.org/keywords/ringing-artifacts","display_name":"Ringing artifacts","score":0.703499972820282},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.6355999708175659},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5619999766349792},{"id":"https://openalex.org/keywords/compression-artifact","display_name":"Compression artifact","score":0.5314000248908997},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.5103999972343445},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.45559999346733093}],"concepts":[{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.7750999927520752},{"id":"https://openalex.org/C30684385","wikidata":"https://www.wikidata.org/wiki/Q176509","display_name":"Ringing","level":3,"score":0.7724000215530396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7139999866485596},{"id":"https://openalex.org/C17828673","wikidata":"https://www.wikidata.org/wiki/Q7334899","display_name":"Ringing artifacts","level":3,"score":0.703499972820282},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6888999938964844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6434999704360962},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.6355999708175659},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5619999766349792},{"id":"https://openalex.org/C57654395","wikidata":"https://www.wikidata.org/wiki/Q1097775","display_name":"Compression artifact","level":5,"score":0.5314000248908997},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.5103999972343445},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.45559999346733093},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4226999878883362},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.420199990272522},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.35989999771118164},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.35760000348091125},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3361000120639801},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2741999924182892},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2655999958515167}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2312/egmm/mm04/105-113","is_oa":true,"landing_page_url":"https://doi.org/10.2312/egmm/mm04/105-113","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.2312/egmm/mm04/105-113","is_oa":true,"landing_page_url":"https://doi.org/10.2312/egmm/mm04/105-113","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"quantization":[1,104],"procedure":[2],"of":[3,51,80,86,107,148],"block-based":[4],"discrete":[5],"cosine":[6],"transform":[7],"(BDCT)":[8],"compression":[9],"(such":[10],"as":[11,70],"JPEG)":[12],"introduces":[13],"annoying":[14],"visual":[15],"artifact.":[16],"In":[17,61],"this":[18],"paper,":[19],"we":[20,99,113],"propose":[21],"a":[22,71,90,144],"novel":[23],"training-based":[24],"method":[25,136],"to":[26],"reduce":[27],"the":[28,49,62,65,78,95,101,109,130],"ringing":[29,52],"artifact":[30,53,87,97,142],"in":[31],"BDCT-encoded":[32],"high-contrast":[33],"images":[34],"(images":[35],"with":[36],"large":[37],"smooth":[38],"color":[39],"areas":[40],"and":[41,125],"strong":[42],"edges/outlines).":[43],"Our":[44],"main":[45],"focus":[46],"is":[47,55,68,127,137],"on":[48],"removal":[50],"that":[54,120],"seldom":[56],"addressed":[57],"by":[58,82],"existing":[59],"methods.":[60],"proposed":[63,131],"method,":[64],"contaminated":[66,111],"image":[67],"modeled":[69],"Markov":[72],"random":[73],"field":[74],"(MRF).":[75],"We":[76,118],"\u0091learn\u0092":[77],"behavior":[79],"contamination":[81],"extracting":[83],"massive":[84],"number":[85],"patterns":[88],"from":[89],"training":[91],"set.":[92],"To":[93],"organize":[94],"extracted":[96],"patterns,":[98],"use":[100],"tree-structured":[102],"vector":[103],"(TSVQ).":[105],"Instead":[106],"post-filtering":[108],"input":[110],"image,":[112],"synthesize":[114],"an":[115],"artifact-reduced":[116],"image.":[117],"show":[119],"substantial":[121],"improvement":[122],"(both":[123],"statistical":[124],"visual)":[126],"achieved":[128],"using":[129],"method.":[132],"Moreover,":[133],"since":[134],"our":[135],"non-iterative,":[138],"it":[139],"can":[140],"remove":[141],"within":[143],"very":[145],"short":[146],"period":[147],"time.":[149]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
