{"id":"https://openalex.org/W2539553977","doi":"https://doi.org/10.1109/acpr.2015.7486612","title":"Blind image quality assessment via a two-stage non-parametric framework","display_name":"Blind image quality assessment via a two-stage non-parametric framework","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W2539553977","doi":"https://doi.org/10.1109/acpr.2015.7486612","mag":"2539553977"},"language":"en","primary_location":{"id":"doi:10.1109/acpr.2015.7486612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2015.7486612","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)","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/A5004098473","display_name":"Redzuan Abdul Manap","orcid":"https://orcid.org/0000-0003-4166-9790"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Redzuan Abdul Manap","raw_affiliation_strings":["The University of Sheffield, Sheffield, United Kingdom"],"affiliations":[{"raw_affiliation_string":"The University of Sheffield, Sheffield, United Kingdom","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049192404","display_name":"Alejandro F. Frangi","orcid":"https://orcid.org/0000-0002-2675-528X"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Alejandro F. Frangi","raw_affiliation_strings":["The University of Sheffield, Sheffield, United Kingdom"],"affiliations":[{"raw_affiliation_string":"The University of Sheffield, Sheffield, United Kingdom","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ling Shao Northumbria","orcid":null},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ling Shao Northumbria","raw_affiliation_strings":["Northumbria University, Newcastle upon Tyne, Tyne and Wear, GB"],"affiliations":[{"raw_affiliation_string":"Northumbria University, Newcastle upon Tyne, Tyne and Wear, GB","institution_ids":["https://openalex.org/I32394136"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004098473"],"corresponding_institution_ids":["https://openalex.org/I91136226"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23764343,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"796","last_page":"800"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":1.0,"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":1.0,"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":0.9947999715805054,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9911999702453613,"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":0.634003758430481},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6331533193588257},{"id":"https://openalex.org/keywords/quality-score","display_name":"Quality Score","score":0.6168195009231567},{"id":"https://openalex.org/keywords/mean-opinion-score","display_name":"Mean opinion score","score":0.5999507904052734},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.594026505947113},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.584372878074646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.583030641078949},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5453583002090454},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.49143731594085693},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46166521310806274},{"id":"https://openalex.org/keywords/standard-test-image","display_name":"Standard test image","score":0.4499182105064392},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.43664291501045227},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36943215131759644},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.24821853637695312},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24063342809677124},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1686379313468933},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.150751531124115},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07344326376914978}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.634003758430481},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6331533193588257},{"id":"https://openalex.org/C2779346075","wikidata":"https://www.wikidata.org/wiki/Q7268763","display_name":"Quality Score","level":3,"score":0.6168195009231567},{"id":"https://openalex.org/C62897895","wikidata":"https://www.wikidata.org/wiki/Q1915482","display_name":"Mean opinion score","level":3,"score":0.5999507904052734},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.594026505947113},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.584372878074646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.583030641078949},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5453583002090454},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.49143731594085693},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46166521310806274},{"id":"https://openalex.org/C180462255","wikidata":"https://www.wikidata.org/wiki/Q3559736","display_name":"Standard test image","level":4,"score":0.4499182105064392},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.43664291501045227},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36943215131759644},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.24821853637695312},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24063342809677124},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1686379313468933},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.150751531124115},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07344326376914978},{"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/acpr.2015.7486612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2015.7486612","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:nrl.northumbria.ac.uk:27464","is_oa":false,"landing_page_url":"http://nrl.northumbria.ac.uk/id/eprint/27464/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401884","display_name":"Northumbria Research Link (Northumbria University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32394136","host_organization_name":"Northumbria University","host_organization_lineage":["https://openalex.org/I32394136"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"},{"id":"pmh:oai:pure.atira.dk:publications/b68c5a27-7829-4f04-908f-2e1abeeb8232","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/b68c5a27-7829-4f04-908f-2e1abeeb8232","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Manap , R A , Frangi , A F & Shao , L 2016 , Blind image quality assessment via a two-stage non-parametric framework . in Proceedings - 3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015 . , 7486612 , Proceedings - 3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015 , IEEE , pp. 796-800 , 3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015 , Kuala Lumpur , Malaysia , 3/11/16 . https://doi.org/10.1109/ACPR.2015.7486612","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322873","display_name":"Universiti Teknikal Malaysia Melaka","ror":"https://ror.org/01xb6rs26"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1922292441","https://openalex.org/W1977246677","https://openalex.org/W1980403059","https://openalex.org/W1982471090","https://openalex.org/W1987489060","https://openalex.org/W2003115311","https://openalex.org/W2006902599","https://openalex.org/W2051596736","https://openalex.org/W2061513831","https://openalex.org/W2080945169","https://openalex.org/W2107476778","https://openalex.org/W2129644086","https://openalex.org/W2134963900","https://openalex.org/W2143901157","https://openalex.org/W2151103935","https://openalex.org/W2153635508","https://openalex.org/W2162692770","https://openalex.org/W2163370434","https://openalex.org/W2166742463","https://openalex.org/W3182211633","https://openalex.org/W6647225686","https://openalex.org/W6798736878"],"related_works":["https://openalex.org/W2033549879","https://openalex.org/W2013629269","https://openalex.org/W3194862240","https://openalex.org/W2096935541","https://openalex.org/W2044558236","https://openalex.org/W4221158116","https://openalex.org/W2943685190","https://openalex.org/W4391020683","https://openalex.org/W4226186675","https://openalex.org/W2539553977"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,12,35,105],"no-reference":[4],"image":[5,29],"quality":[6,59,80,108],"assessment":[7],"(NR-IQA)":[8],"algorithm":[9,88,100,132],"based":[10,38],"on":[11,122],"two-stage":[13],"non-parametric":[14],"framework":[15],"is":[16,31,64,89,96,110],"presented.":[17],"At":[18],"the":[19,22,27,41,50,54,58,79,83,99,116,123,130],"first":[20,32],"stage,":[21],"type":[23],"of":[24,60,82,104,115],"distortion":[25,56],"affecting":[26],"test":[28,62,84],"patches":[30,52],"identified":[33,55],"via":[34],"nearest-neighbor":[36],"(NN)":[37],"classifier.":[39],"Utilizing":[40],"differential":[42],"mean":[43],"opinion":[44],"score":[45,81],"(DMOS)":[46],"values":[47],"associated":[48],"with":[49,135],"labelled":[51],"within":[53],"class,":[57],"each":[61],"patch":[63],"then":[65,74],"predicted":[66,71],"using":[67],"k-NN":[68],"regression.":[69],"The":[70,86],"scores":[72],"are":[73],"pooled":[75],"together":[76],"to":[77,143],"obtain":[78],"image.":[85],"proposed":[87,131],"simple":[90],"yet":[91],"effective.":[92],"No":[93],"training":[94],"phase":[95],"required":[97],"and":[98,139],"also":[101],"offers":[102],"prediction":[103],"local":[106],"region's":[107],"which":[109],"not":[111],"available":[112],"in":[113],"most":[114],"previous":[117],"NR-IQA":[118,145],"methods.":[119],"Experimental":[120],"results":[121],"standard":[124],"LIVE":[125],"IQA":[126],"database":[127],"indicate":[128],"that":[129],"correlates":[133],"highly":[134],"human":[136],"perceptual":[137],"measures":[138],"deliver":[140],"competitive":[141],"performance":[142],"state-of-the-art":[144],"algorithms.":[146]},"counts_by_year":[],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}