{"id":"https://openalex.org/W3195117819","doi":"https://doi.org/10.1109/icip42928.2021.9506498","title":"An Effective Sharpness Assessment Method For Shallow Depth-Of-Field Images","display_name":"An Effective Sharpness Assessment Method For Shallow Depth-Of-Field Images","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W3195117819","doi":"https://doi.org/10.1109/icip42928.2021.9506498","mag":"3195117819"},"language":"en","primary_location":{"id":"doi:10.1109/icip42928.2021.9506498","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506498","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5028187551","display_name":"Zhixiang Duan","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixiang Duan","raw_affiliation_strings":["Xidian University,School of Computer Science and Technology,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,School of Computer Science and Technology,Xi’an,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054260188","display_name":"Guangxin Li","orcid":"https://orcid.org/0000-0002-3911-8255"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangxin Li","raw_affiliation_strings":["Xidian University,School of Computer Science and Technology,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,School of Computer Science and Technology,Xi’an,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016996180","display_name":"Guoliang Fan","orcid":"https://orcid.org/0000-0002-8584-9040"},"institutions":[{"id":"https://openalex.org/I115475287","display_name":"Oklahoma State University","ror":"https://ror.org/01g9vbr38","country_code":"US","type":"education","lineage":["https://openalex.org/I115475287"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guoliang Fan","raw_affiliation_strings":["Oklahoma State University,School of Electrical and Computer Engineering,Stillwater,USA","School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Oklahoma State University,School of Electrical and Computer Engineering,Stillwater,USA","institution_ids":["https://openalex.org/I115475287"]},{"raw_affiliation_string":"School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, USA","institution_ids":["https://openalex.org/I115475287"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.097,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.39473557,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1449","last_page":"1453"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9983000159263611,"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":0.9961000084877014,"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/metric","display_name":"Metric (unit)","score":0.7574018836021423},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.70616215467453},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6582008004188538},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6418936252593994},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5736328959465027},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5668832063674927},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5480353236198425},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5219975709915161},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5133968591690063},{"id":"https://openalex.org/keywords/quality-assessment","display_name":"Quality assessment","score":0.4358091354370117},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3368738889694214},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18859192728996277},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06732630729675293}],"concepts":[{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7574018836021423},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.70616215467453},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6582008004188538},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6418936252593994},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5736328959465027},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5668832063674927},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5480353236198425},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5219975709915161},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5133968591690063},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.4358091354370117},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3368738889694214},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18859192728996277},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06732630729675293},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip42928.2021.9506498","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506498","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1486810742","https://openalex.org/W1982471090","https://openalex.org/W2008051965","https://openalex.org/W2014305476","https://openalex.org/W2057546802","https://openalex.org/W2073623229","https://openalex.org/W2085448797","https://openalex.org/W2102166818","https://openalex.org/W2105143518","https://openalex.org/W2134963900","https://openalex.org/W2138088051","https://openalex.org/W2161907179","https://openalex.org/W2168023013","https://openalex.org/W2171220523","https://openalex.org/W2615691989","https://openalex.org/W2886239594","https://openalex.org/W2970132594","https://openalex.org/W2971143963","https://openalex.org/W3089885221","https://openalex.org/W6684791271"],"related_works":["https://openalex.org/W3135697610","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W1647606319","https://openalex.org/W2466958844","https://openalex.org/W2804751933","https://openalex.org/W2245293081","https://openalex.org/W1973829424","https://openalex.org/W3209787365"],"abstract_inverted_index":{"No-reference":[0],"(NR)":[1],"image":[2,10,81],"sharpness":[3,20,46,82,106],"assessment":[4,12,21,47,83],"is":[5,95],"an":[6,77],"important":[7],"issue":[8],"for":[9,55],"quality":[11],"and":[13,135],"algorithm":[14,118,140],"performance":[15],"evaluation.":[16],"Many":[17],"objective":[18,80],"NR":[19],"metrics":[22],"have":[23],"been":[24],"proposed":[25,117,139],"which":[26],"are":[27,63],"often":[28,64],"intended":[29],"to":[30,66],"be":[31,112],"strongly":[32],"associated":[33],"with":[34,57,115,143],"the":[35,51,68,72,87,102,105,116,138],"human":[36],"visual":[37],"system":[38],"(HVS).":[39],"However,":[40],"recent":[41],"studies":[42],"show":[43],"that":[44,62,94],"common":[45],"indicators":[48],"may":[49],"misjudge":[50],"degree":[52],"of":[53,60,89,107,137],"blurring":[54],"images":[56,110],"shallow":[58,108],"depth":[59],"field":[61],"used":[65],"highlight":[67],"main":[69],"subject":[70],"in":[71],"view.":[73],"This":[74,99],"paper":[75,100],"proposes":[76],"efficient":[78],"no-reference":[79],"metric":[84],"based":[85],"on":[86,129],"product":[88],"bidirectional":[90],"pixel":[91],"intensity":[92],"differences":[93],"computed":[96],"block-by-block":[97],"(PBDB).":[98],"contributes":[101],"following:":[103],"(1)":[104],"depth-of-field":[109],"can":[111],"accurately":[113],"evaluated":[114],"when":[119,141],"traditional":[120],"methods":[121],"do":[122],"not":[123],"work":[124],"well.":[125],"(2)":[126],"Experimental":[127],"results":[128],"three":[130],"public":[131],"datasets":[132],"demonstrate":[133],"competitiveness":[134],"effectiveness":[136],"compared":[142],"several":[144],"state-of-the-art":[145],"methods.":[146]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}