{"id":"https://openalex.org/W2144866068","doi":"https://doi.org/10.1109/icip.2009.5413957","title":"Objective perceptual video quality measurement method based on hybrid no reference framework","display_name":"Objective perceptual video quality measurement method based on hybrid no reference framework","publication_year":2009,"publication_date":"2009-11-01","ids":{"openalex":"https://openalex.org/W2144866068","doi":"https://doi.org/10.1109/icip.2009.5413957","mag":"2144866068"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2009.5413957","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5413957","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"article","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/A5102256120","display_name":"Osamu Sugimoto","orcid":null},"institutions":[{"id":"https://openalex.org/I71799228","display_name":"KDDI (Japan)","ror":"https://ror.org/03r7fm174","country_code":"JP","type":"company","lineage":["https://openalex.org/I71799228"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Osamu Sugimoto","raw_affiliation_strings":["KDDI R&D Laboratories Inc","KDDI R&D Laboratories Inc., Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI R&D Laboratories Inc","institution_ids":["https://openalex.org/I71799228"]},{"raw_affiliation_string":"KDDI R&D Laboratories Inc., Japan","institution_ids":["https://openalex.org/I71799228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102261183","display_name":"Naito Sei","orcid":null},"institutions":[{"id":"https://openalex.org/I71799228","display_name":"KDDI (Japan)","ror":"https://ror.org/03r7fm174","country_code":"JP","type":"company","lineage":["https://openalex.org/I71799228"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naito Sei","raw_affiliation_strings":["KDDI R&D Laboratories Inc., Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI R&D Laboratories Inc., Japan","institution_ids":["https://openalex.org/I71799228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068660571","display_name":"Shigeyuki Sakazawa","orcid":null},"institutions":[{"id":"https://openalex.org/I71799228","display_name":"KDDI (Japan)","ror":"https://ror.org/03r7fm174","country_code":"JP","type":"company","lineage":["https://openalex.org/I71799228"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sakazawa Shigeyuki","raw_affiliation_strings":["KDDI R&D Laboratories Inc., Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI R&D Laboratories Inc., Japan","institution_ids":["https://openalex.org/I71799228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019962362","display_name":"Koike Atsushi","orcid":null},"institutions":[{"id":"https://openalex.org/I6030618","display_name":"Seikei University","ror":"https://ror.org/03ptaj492","country_code":"JP","type":"education","lineage":["https://openalex.org/I6030618"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koike Atsushi","raw_affiliation_strings":["Seikei University, Japan","SEIKEI University, Japan#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seikei University, Japan","institution_ids":["https://openalex.org/I6030618"]},{"raw_affiliation_string":"SEIKEI University, Japan#TAB#","institution_ids":["https://openalex.org/I6030618"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9418,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.94347485,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2237","last_page":"2240"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998000264167786,"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/T11165","display_name":"Image and Video Quality Assessment","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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9980000257492065,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9966999888420105,"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/bitstream","display_name":"Bitstream","score":0.8634913563728333},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7661077976226807},{"id":"https://openalex.org/keywords/baseband","display_name":"Baseband","score":0.7509428262710571},{"id":"https://openalex.org/keywords/video-quality","display_name":"Video quality","score":0.7145169973373413},{"id":"https://openalex.org/keywords/subjective-video-quality","display_name":"Subjective video quality","score":0.6386356353759766},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.624186635017395},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6095625162124634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5067690014839172},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.48290038108825684},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4646337330341339},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.45449769496917725},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4481474757194519},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4283265769481659},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33209505677223206},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3211715817451477},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.25455909967422485},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2526405453681946},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20347917079925537},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.1095813512802124},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09947454929351807}],"concepts":[{"id":"https://openalex.org/C136695289","wikidata":"https://www.wikidata.org/wiki/Q415568","display_name":"Bitstream","level":3,"score":0.8634913563728333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7661077976226807},{"id":"https://openalex.org/C65165936","wikidata":"https://www.wikidata.org/wiki/Q575784","display_name":"Baseband","level":3,"score":0.7509428262710571},{"id":"https://openalex.org/C103910844","wikidata":"https://www.wikidata.org/wiki/Q2631256","display_name":"Video quality","level":3,"score":0.7145169973373413},{"id":"https://openalex.org/C114227958","wikidata":"https://www.wikidata.org/wiki/Q7631422","display_name":"Subjective video quality","level":4,"score":0.6386356353759766},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.624186635017395},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6095625162124634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5067690014839172},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.48290038108825684},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4646337330341339},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.45449769496917725},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4481474757194519},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4283265769481659},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33209505677223206},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3211715817451477},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.25455909967422485},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2526405453681946},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20347917079925537},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.1095813512802124},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09947454929351807},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2009.5413957","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5413957","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1541874523","https://openalex.org/W2107476778","https://openalex.org/W2114586165","https://openalex.org/W2128770501","https://openalex.org/W2129889344","https://openalex.org/W2143029530","https://openalex.org/W2154799811","https://openalex.org/W2168756588","https://openalex.org/W3214220970","https://openalex.org/W6632322077","https://openalex.org/W6676199892"],"related_works":["https://openalex.org/W2133665775","https://openalex.org/W1976986287","https://openalex.org/W2125774922","https://openalex.org/W1580932091","https://openalex.org/W2149138362","https://openalex.org/W1998281041","https://openalex.org/W1973175507","https://openalex.org/W1579539036","https://openalex.org/W2113264056","https://openalex.org/W1573226396","https://openalex.org/W2081148648","https://openalex.org/W2036884885","https://openalex.org/W2158524994","https://openalex.org/W2138217668","https://openalex.org/W2119869354","https://openalex.org/W2107476778","https://openalex.org/W2085518012","https://openalex.org/W2040857266","https://openalex.org/W1995760011","https://openalex.org/W2026208768"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"the":[3,11,30,45,52,57,61,71,80,88,92,100,105,115,126],"authors":[4],"propose":[5],"a":[6,109,123,130],"novel":[7],"method":[8,66,102],"to":[9,55,86,121],"measure":[10],"perceived":[12],"picture":[13,54],"quality":[14,40,90,107,128],"of":[15,51,60,112,133],"H.264":[16],"coded":[17],"video":[18,39],"based":[19],"on":[20],"hybrid":[21],"no":[22],"reference":[23],"framework.":[24],"The":[25,64],"latter":[26],"term":[27],"means":[28],"that":[29],"proposed":[31,65,101],"model":[32],"uses":[33],"only":[34],"receiver-side":[35],"information":[36,69],"for":[37],"objective":[38],"assessment,":[41],"but":[42],"analyzes":[43],"both":[44],"compressed":[46],"bitstream":[47],"and":[48],"baseband":[49,81],"signals":[50],"decoded":[53],"improve":[56],"estimation":[58],"accuracy":[59],"subjective":[62,106,127],"quality.":[63],"extracts":[67],"quantizer-scale":[68],"from":[70,79],"bit-stream":[72],"along":[73],"with":[74],"two":[75],"spatiotemporal":[76],"image":[77],"features":[78],"signal,":[82],"which":[83,118],"are":[84],"integrated":[85],"express":[87],"overall":[89],"using":[91],"weighted":[93],"Minkowski":[94],"metric.":[95],"A":[96],"computer":[97],"simulation":[98],"shows":[99],"can":[103],"estimate":[104],"at":[108,129],"correlation":[110,131],"coefficient":[111,132],"0.909":[113],"whereas":[114],"PSNR":[116],"metric,":[117],"is":[119],"referred":[120],"as":[122],"benchmark,":[124],"correlates":[125],"0.773.":[134]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
