{"id":"https://openalex.org/W2578448101","doi":"https://doi.org/10.1109/apsipa.2016.7820878","title":"Light field upsampling by joint bilateral filtering on epipolar plane images","display_name":"Light field upsampling by joint bilateral filtering on epipolar plane images","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2578448101","doi":"https://doi.org/10.1109/apsipa.2016.7820878","mag":"2578448101"},"language":"en","primary_location":{"id":"doi:10.1109/apsipa.2016.7820878","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2016.7820878","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)","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/A5089025176","display_name":"Hao-Chiang Shao","orcid":"https://orcid.org/0000-0002-3749-234X"},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Hao-Chiang Shao","raw_affiliation_strings":["Institute of Information Science, Academia Sinica, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Information Science, Academia Sinica, Taiwan","institution_ids":["https://openalex.org/I4210098366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058554535","display_name":"Wen-Liang Hwang","orcid":"https://orcid.org/0000-0002-5546-6575"},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wen-Liang Hwang","raw_affiliation_strings":["Institute of Information Science, Academia Sinica, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Information Science, Academia Sinica, Taiwan","institution_ids":["https://openalex.org/I4210098366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089025176"],"corresponding_institution_ids":["https://openalex.org/I4210098366"],"apc_list":null,"apc_paid":null,"fwci":0.167,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.60308457,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"27","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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/T10531","display_name":"Advanced Vision and Imaging","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/T11019","display_name":"Image Enhancement 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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9973999857902527,"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/upsampling","display_name":"Upsampling","score":0.9210388660430908},{"id":"https://openalex.org/keywords/epipolar-geometry","display_name":"Epipolar geometry","score":0.8312112092971802},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7050543427467346},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6821836829185486},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6526362895965576},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5277296304702759},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5150699019432068},{"id":"https://openalex.org/keywords/light-field","display_name":"Light field","score":0.505704402923584},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5018594264984131},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.437578946352005},{"id":"https://openalex.org/keywords/plane","display_name":"Plane (geometry)","score":0.4278740882873535},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.4220293164253235},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39909878373146057},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2665407061576843},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.19676995277404785},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.10419830679893494}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.9210388660430908},{"id":"https://openalex.org/C23379248","wikidata":"https://www.wikidata.org/wiki/Q200904","display_name":"Epipolar geometry","level":3,"score":0.8312112092971802},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7050543427467346},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6821836829185486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6526362895965576},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5277296304702759},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5150699019432068},{"id":"https://openalex.org/C48983235","wikidata":"https://www.wikidata.org/wiki/Q593161","display_name":"Light field","level":2,"score":0.505704402923584},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5018594264984131},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.437578946352005},{"id":"https://openalex.org/C17825722","wikidata":"https://www.wikidata.org/wiki/Q17285","display_name":"Plane (geometry)","level":2,"score":0.4278740882873535},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.4220293164253235},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39909878373146057},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2665407061576843},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.19676995277404785},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.10419830679893494},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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},{"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/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/apsipa.2016.7820878","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2016.7820878","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321041","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1481550144","https://openalex.org/W1924797782","https://openalex.org/W1994574914","https://openalex.org/W2006262236","https://openalex.org/W2014627134","https://openalex.org/W2028778909","https://openalex.org/W2039628335","https://openalex.org/W2046321681","https://openalex.org/W2060167709","https://openalex.org/W2064586097","https://openalex.org/W2081385919","https://openalex.org/W2104600947","https://openalex.org/W2105198794","https://openalex.org/W2128268941","https://openalex.org/W2137313943","https://openalex.org/W2150007820","https://openalex.org/W2162162078","https://openalex.org/W4241716071","https://openalex.org/W4250780936","https://openalex.org/W6680152570"],"related_works":["https://openalex.org/W4385805064","https://openalex.org/W2929681741","https://openalex.org/W2594336302","https://openalex.org/W3004135429","https://openalex.org/W2787003719","https://openalex.org/W3209881651","https://openalex.org/W3121005460","https://openalex.org/W2294274695","https://openalex.org/W2744012867","https://openalex.org/W4292830147"],"abstract_inverted_index":{"Due":[0],"to":[1,41,70],"the":[2,9,25,30,48,63,79,91,103,125],"trade-off":[3],"between":[4],"spatial":[5,11],"and":[6,113,161],"angular":[7],"resolution,":[8],"effective":[10],"resolution":[12],"of":[13,24,27,51,66,90,128,149],"a":[14,38,43,135,147],"light":[15,44,137],"field":[16,45,138],"image":[17,80,105],"is":[18,69,94,110,131],"usually":[19],"less":[20],"than":[21,118],"one":[22],"percent":[23],"number":[26],"pixels":[28],"on":[29,58],"photo":[31],"sensor.":[32],"In":[33],"this":[34,129],"paper,":[35],"we":[36],"propose":[37],"prototype":[39],"algorithm":[40,93],"upsample":[42],"image.":[46],"Because":[47],"boundary":[49,86],"edges":[50],"3D":[52],"objects":[53],"would":[54],"result":[55],"in":[56,159],"lines":[57],"epipolar":[59],"plane":[60],"images":[61],"(EPIs),":[62],"main":[64,126],"idea":[65],"our":[67,108],"method":[68,109,130],"preserve":[71],"these":[72],"line":[73],"structures":[74],"while":[75],"upsampling":[76,144,152],"so":[77],"that":[78,102,132,154],"enlargement":[81],"can":[82,155],"still":[83,111],"have":[84],"sharp":[85],"edges.":[87],"The":[88],"kernel":[89],"proposed":[92],"an":[95],"iterative":[96],"joint-bilateral":[97],"filtering":[98],"process.":[99],"Experiments":[100],"show":[101],"upsampled":[104],"derived":[106,120],"by":[107,121],"refocusable":[112],"has":[114],"better":[115],"visual":[116],"quality":[117],"those":[119],"other":[122],"methods.":[123],"Finally,":[124],"contribution":[127],"it":[133],"decomposes":[134],"4D":[136],"space":[139],"L(u,":[140],"v,":[141],"s,":[142],"t)":[143],"problem":[145],"into":[146],"series":[148],"1D,":[150],"parameter-free":[151],"subproblems":[153],"be":[156],"solved":[157],"fast":[158],"u-s":[160],"v-t":[162],"EPI":[163],"domains.":[164]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
