{"id":"https://openalex.org/W2573126958","doi":"https://doi.org/10.1109/vcip.2016.7805563","title":"Method to quality assessment of stereo images","display_name":"Method to quality assessment of stereo images","publication_year":2016,"publication_date":"2016-11-01","ids":{"openalex":"https://openalex.org/W2573126958","doi":"https://doi.org/10.1109/vcip.2016.7805563","mag":"2573126958"},"language":"en","primary_location":{"id":"doi:10.1109/vcip.2016.7805563","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2016.7805563","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Visual Communications and Image Processing (VCIP)","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/A5101879994","display_name":"Jian Ma","orcid":"https://orcid.org/0000-0003-4743-7923"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Ma","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060120489","display_name":"Ping An","orcid":"https://orcid.org/0000-0002-4995-728X"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping An","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101879994"],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":0.334,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68425999,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"4"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9812999963760376,"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/T11666","display_name":"Color Science and Applications","score":0.9789000153541565,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.7945458292961121},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7936054468154907},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7048799991607666},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.6803833246231079},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6795443296432495},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6574497222900391},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.6377341151237488},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6041848063468933},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5525804758071899},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5049548745155334},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4667155146598816},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.46240168809890747},{"id":"https://openalex.org/keywords/stereopsis","display_name":"Stereopsis","score":0.4443954825401306},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.43227052688598633},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4035632014274597},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33540254831314087},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3141130208969116},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.11377936601638794},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06032171845436096},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.059422045946121216}],"concepts":[{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.7945458292961121},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7936054468154907},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7048799991607666},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.6803833246231079},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6795443296432495},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6574497222900391},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.6377341151237488},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6041848063468933},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5525804758071899},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5049548745155334},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4667155146598816},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.46240168809890747},{"id":"https://openalex.org/C68537008","wikidata":"https://www.wikidata.org/wiki/Q247932","display_name":"Stereopsis","level":2,"score":0.4443954825401306},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.43227052688598633},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4035632014274597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33540254831314087},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3141130208969116},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.11377936601638794},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06032171845436096},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.059422045946121216},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"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/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip.2016.7805563","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2016.7805563","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W3758953","https://openalex.org/W1513661237","https://openalex.org/W1580389772","https://openalex.org/W1930650491","https://openalex.org/W1971992046","https://openalex.org/W1981076008","https://openalex.org/W1993705360","https://openalex.org/W2019217164","https://openalex.org/W2064875844","https://openalex.org/W2070322626","https://openalex.org/W2073812468","https://openalex.org/W2099308462","https://openalex.org/W2129331753","https://openalex.org/W2133665775","https://openalex.org/W2161907179","https://openalex.org/W2168078737","https://openalex.org/W2171349048","https://openalex.org/W2293651521","https://openalex.org/W2295037606","https://openalex.org/W2626610348","https://openalex.org/W2951413051","https://openalex.org/W6634589695"],"related_works":["https://openalex.org/W2398548367","https://openalex.org/W2064421702","https://openalex.org/W2017236227","https://openalex.org/W2510234973","https://openalex.org/W1998629164","https://openalex.org/W1963814307","https://openalex.org/W2051061664","https://openalex.org/W2035520273","https://openalex.org/W2014735529","https://openalex.org/W14464361"],"abstract_inverted_index":{"In":[0,85,99],"this":[1,29],"paper,":[2],"we":[3],"propose":[4],"a":[5,76,109,122],"novel":[6],"full":[7],"reference":[8],"image":[9],"quality":[10,27,72,116,128],"assessment":[11],"model":[12,30,143],"for":[13,25],"stereo":[14,26,130],"images.":[15,131],"To":[16],"improve":[17],"the":[18,34,47,52,63,69,80,86,89,100,103,115,118,141],"characteristics":[19],"of":[20,33,79,125,129],"human":[21],"vision":[22],"system":[23],"(HVS)":[24],"analysis,":[28],"exploits":[31],"mechanism":[32],"HVS":[35],"from":[36,82,117],"three":[37,135],"aspects:":[38],"1)":[39],"apply":[40],"contrast":[41,111],"sensitivity":[42],"function":[43],"(CSF)":[44],"filtering":[45],"on":[46,62,94,108,134],"two":[48,64,83,119],"monocular":[49,65],"views.":[50],"2)":[51],"conventional":[53],"2D":[54],"MAD":[55],"(most":[56],"apparent":[57],"distortion)":[58],"algorithm":[59],"is":[60,73],"applied":[61],"views,":[66],"and":[67],"then":[68],"combined":[70],"binocular":[71,95],"estimated":[74],"via":[75],"weighted":[77],"sum":[78],"estimates":[81],"stages.":[84],"first":[87],"stage,":[88,102],"weights":[90,104],"are":[91,105],"determined":[92,106],"based":[93,107],"phase":[96],"congruency":[97],"measure.":[98,112],"second":[101],"block-based":[110],"3)":[113],"combine":[114],"stages":[120],"into":[121],"single":[123],"estimate":[124],"overall":[126],"perceived":[127],"Experimental":[132],"results":[133],"public":[136],"benchmark":[137],"databases":[138],"show":[139],"that":[140],"proposed":[142],"achieves":[144],"significantly":[145],"higher":[146],"consistency":[147],"with":[148],"subjective":[149],"scores.":[150]},"counts_by_year":[{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}