{"id":"https://openalex.org/W2948229603","doi":"https://doi.org/10.2352/issn.2470-1173.2019.11.ipas-261","title":"Evaluating the effectiveness of image quality metrics in a light field scenario","display_name":"Evaluating the effectiveness of image quality metrics in a light field scenario","publication_year":2019,"publication_date":"2019-01-13","ids":{"openalex":"https://openalex.org/W2948229603","doi":"https://doi.org/10.2352/issn.2470-1173.2019.11.ipas-261","mag":"2948229603"},"language":"en","primary_location":{"id":"doi:10.2352/issn.2470-1173.2019.11.ipas-261","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2019.11.ipas-261","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-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/A5014627170","display_name":"Giuliano Arru","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Giuliano Arru","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044389627","display_name":"Federica Battisti","orcid":"https://orcid.org/0000-0002-0846-5879"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Federica Battisti","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5028830723","display_name":"Marco Carli","orcid":"https://orcid.org/0000-0002-7489-3767"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marco Carli","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5014627170"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.0424893,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"31","issue":"11","first_page":"261","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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"}},"topics":[{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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/T11165","display_name":"Image and Video Quality Assessment","score":0.9976000189781189,"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/distortion","display_name":"Distortion (music)","score":0.7898578643798828},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.7677103877067566},{"id":"https://openalex.org/keywords/light-field","display_name":"Light field","score":0.7621611952781677},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6172492504119873},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5965795516967773},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5839245915412903},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.573885977268219},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5612281560897827},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5376715660095215},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5312385559082031},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.47218313813209534},{"id":"https://openalex.org/keywords/depth-of-field","display_name":"Depth of field","score":0.4447338581085205},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3755713701248169},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3218191862106323},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3199736773967743},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09537190198898315},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0873742401599884}],"concepts":[{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.7898578643798828},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7677103877067566},{"id":"https://openalex.org/C48983235","wikidata":"https://www.wikidata.org/wiki/Q593161","display_name":"Light field","level":2,"score":0.7621611952781677},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6172492504119873},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5965795516967773},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5839245915412903},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.573885977268219},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5612281560897827},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5376715660095215},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5312385559082031},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.47218313813209534},{"id":"https://openalex.org/C183072630","wikidata":"https://www.wikidata.org/wiki/Q215932","display_name":"Depth of field","level":2,"score":0.4447338581085205},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3755713701248169},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3218191862106323},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3199736773967743},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09537190198898315},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0873742401599884},{"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"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/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"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/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.2352/issn.2470-1173.2019.11.ipas-261","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2019.11.ipas-261","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-article"},{"id":"pmh:oai:www.research.unipd.it:11577/3363422","is_oa":false,"landing_page_url":"http://hdl.handle.net/11577/3363422","pdf_url":null,"source":{"id":"https://openalex.org/S4306402547","display_name":"Padua Research Archive (University of Padova)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2580863105","https://openalex.org/W2784261531","https://openalex.org/W2288907727","https://openalex.org/W2997982366","https://openalex.org/W2334078434","https://openalex.org/W3001631268","https://openalex.org/W3142456067","https://openalex.org/W4320732222","https://openalex.org/W4297921476","https://openalex.org/W4251977926"],"abstract_inverted_index":{"In":[0],"this":[1],"contribution,":[2],"an":[3],"objective":[4],"metric":[5],"for":[6],"quality":[7],"evaluation":[8],"of":[9,22,26,89],"light":[10,37,52],"field":[11,38,53],"images":[12],"is":[13,17,30,44,59,64],"presented.":[14],"The":[15,41],"method":[16],"based":[18],"on":[19],"the":[20,23,36,48,68,72,83,87,90],"exploitation":[21],"depth":[24,42,69],"information":[25],"a":[27,56,62],"scene,":[28],"that":[29],"captured":[31],"with":[32,71,82],"high":[33],"accuracy":[34],"by":[35,78],"imaging":[39],"system.":[40],"map":[43],"estimated":[45],"both":[46],"from":[47],"original":[49],"and":[50,61],"impaired":[51],"data.":[54],"Then,":[55],"similarity":[57],"measure":[58],"applied,":[60],"mapping":[63],"performed":[65,77],"to":[66],"link":[67],"distortion":[70],"perceived":[73],"quality.":[74],"Experimental":[75],"test":[76],"comparing":[79],"state-of-art":[80],"metrics":[81],"proposed":[84,91],"one,":[85],"demonstrate":[86],"effectiveness":[88],"metric.":[92]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-06-14T00:00:00"}