{"id":"https://openalex.org/W2088069645","doi":"https://doi.org/10.1117/12.2083818","title":"Video pre-processing with JND-based Gaussian filtering of superpixels","display_name":"Video pre-processing with JND-based Gaussian filtering of superpixels","publication_year":2015,"publication_date":"2015-03-04","ids":{"openalex":"https://openalex.org/W2088069645","doi":"https://doi.org/10.1117/12.2083818","mag":"2088069645"},"language":"en","primary_location":{"id":"doi:10.1117/12.2083818","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2083818","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101654842","display_name":"Lei Ding","orcid":"https://orcid.org/0000-0003-2277-267X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Ding","raw_affiliation_strings":["Peking Univ. (China)","Peking Univ, (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking Univ. (China)","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Peking Univ, (China)","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447691","display_name":"Ge Li","orcid":"https://orcid.org/0000-0003-0140-0949"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Li","raw_affiliation_strings":["Peking Univ. (China)","Peking Univ, (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking Univ. (China)","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Peking Univ, (China)","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050071143","display_name":"Ronggang Wang","orcid":"https://orcid.org/0000-0003-0873-0465"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronggang Wang","raw_affiliation_strings":["Peking Univ. (China)","Peking Univ, (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking Univ. (China)","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Peking Univ, (China)","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017052768","display_name":"Wenmin Wang","orcid":"https://orcid.org/0000-0003-2664-4413"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenmin Wang","raw_affiliation_strings":["Peking Univ. (China)","Peking Univ, (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking Univ. (China)","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Peking Univ, (China)","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"9410","issue":null,"first_page":"941004","last_page":"941004"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998999834060669,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9998999834060669,"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/T10741","display_name":"Video Coding and Compression Technologies","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9986000061035156,"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/computer-science","display_name":"Computer science","score":0.7303601503372192},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7289514541625977},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6879562139511108},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6661010980606079},{"id":"https://openalex.org/keywords/luminance","display_name":"Luminance","score":0.6507564187049866},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5903055667877197},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5286260843276978},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.48594582080841064},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4676501452922821},{"id":"https://openalex.org/keywords/gaussian-filter","display_name":"Gaussian filter","score":0.4650830626487732},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2578940987586975}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7303601503372192},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7289514541625977},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6879562139511108},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6661010980606079},{"id":"https://openalex.org/C73313986","wikidata":"https://www.wikidata.org/wiki/Q355386","display_name":"Luminance","level":2,"score":0.6507564187049866},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5903055667877197},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5286260843276978},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.48594582080841064},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4676501452922821},{"id":"https://openalex.org/C65892221","wikidata":"https://www.wikidata.org/wiki/Q1113935","display_name":"Gaussian filter","level":3,"score":0.4650830626487732},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2578940987586975},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2083818","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2083818","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2104350111","https://openalex.org/W2114415799","https://openalex.org/W2114625247","https://openalex.org/W2115416470","https://openalex.org/W2118246710","https://openalex.org/W2136358209","https://openalex.org/W2136477141","https://openalex.org/W2146395539","https://openalex.org/W2156008990","https://openalex.org/W2170682758","https://openalex.org/W6630279123","https://openalex.org/W6677081753","https://openalex.org/W6677719301","https://openalex.org/W6677790645","https://openalex.org/W6680015794","https://openalex.org/W6680248023","https://openalex.org/W6681628524","https://openalex.org/W6682990329"],"related_works":["https://openalex.org/W2609066529","https://openalex.org/W2082319654","https://openalex.org/W1970319972","https://openalex.org/W2150541705","https://openalex.org/W2389710210","https://openalex.org/W4386840168","https://openalex.org/W2921413925","https://openalex.org/W1998409879","https://openalex.org/W2566989475","https://openalex.org/W3166815864"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"an":[3],"innovative":[4],"method":[5,13],"of":[6,34,40,43,55],"HEVC":[7],"video":[8],"pre-processing":[9],"is":[10,61],"proposed.":[11],"The":[12],"applies":[14],"a":[15,23,52],"simple":[16],"linear":[17],"iterative":[18],"clustering":[19,25],"(SLIC),":[20],"which":[21],"adapts":[22],"k-means":[24],"to":[26,73],"group":[27],"pixels":[28],"into":[29],"perceptually":[30],"meaningful":[31],"atomic":[32],"regions":[33],"superpixels.":[35],"By":[36],"calculating":[37],"the":[38,50,59],"average":[39,42],"weighted":[41],"luminance":[44],"differences":[45],"around":[46],"each":[47],"pixel":[48],"in":[49,77],"superpixel,":[51],"suitable":[53],"parameter":[54],"Gaussian":[56],"filter":[57],"for":[58],"superpixel":[60],"determined.":[62],"Experimental":[63],"results":[64],"show":[65],"that":[66],"bit":[67],"rate":[68],"can":[69],"be":[70],"reduced":[71],"up":[72],"29%":[74],"without":[75],"loss":[76],"visual":[78],"quality.":[79]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
