{"id":"https://openalex.org/W2195231623","doi":"https://doi.org/10.1109/tip.2015.2501749","title":"Edge-Guided Single Depth Image Super Resolution","display_name":"Edge-Guided Single Depth Image Super Resolution","publication_year":2015,"publication_date":"2015-11-20","ids":{"openalex":"https://openalex.org/W2195231623","doi":"https://doi.org/10.1109/tip.2015.2501749","mag":"2195231623","pmid":"https://pubmed.ncbi.nlm.nih.gov/26599968"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2015.2501749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2015.2501749","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101791703","display_name":"Jun Xie","orcid":"https://orcid.org/0000-0003-0955-9970"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jun Xie","raw_affiliation_strings":["Department of Electrical Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052325109","display_name":"Rog\u00e9rio Feris","orcid":"https://orcid.org/0000-0001-6399-0679"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rogerio Schmidt Feris","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109127966","display_name":"Ming\u2013Ting Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming-Ting Sun","raw_affiliation_strings":["Department of Electrical Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101791703"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":10.4935,"has_fulltext":false,"cited_by_count":200,"citation_normalized_percentile":{"value":0.98852635,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"25","issue":"1","first_page":"428","last_page":"438"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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/T10531","display_name":"Advanced Vision and Imaging","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/T11105","display_name":"Advanced Image Processing Techniques","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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.8665794730186462},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7449989318847656},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6925845146179199},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6061344146728516},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.5901969075202942},{"id":"https://openalex.org/keywords/depth-map","display_name":"Depth map","score":0.5738446712493896},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.558448076248169},{"id":"https://openalex.org/keywords/image-gradient","display_name":"Image gradient","score":0.4961412847042084},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.4956117868423462},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.4952813684940338},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4863505959510803},{"id":"https://openalex.org/keywords/depth-of-field","display_name":"Depth of field","score":0.4495049715042114},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.41250959038734436},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.39183130860328674},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35602501034736633},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.30170130729675293}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.8665794730186462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7449989318847656},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6925845146179199},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6061344146728516},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.5901969075202942},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.5738446712493896},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.558448076248169},{"id":"https://openalex.org/C182037307","wikidata":"https://www.wikidata.org/wiki/Q17039097","display_name":"Image gradient","level":5,"score":0.4961412847042084},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.4956117868423462},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.4952813684940338},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4863505959510803},{"id":"https://openalex.org/C183072630","wikidata":"https://www.wikidata.org/wiki/Q215932","display_name":"Depth of field","level":2,"score":0.4495049715042114},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.41250959038734436},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.39183130860328674},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35602501034736633},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.30170130729675293}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2015.2501749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2015.2501749","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:26599968","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26599968","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W63091017","https://openalex.org/W1484539719","https://openalex.org/W1518641734","https://openalex.org/W1588041862","https://openalex.org/W1791560514","https://openalex.org/W1872406745","https://openalex.org/W1930824406","https://openalex.org/W1971918169","https://openalex.org/W1993120651","https://openalex.org/W2001395975","https://openalex.org/W2008523386","https://openalex.org/W2020353466","https://openalex.org/W2053812214","https://openalex.org/W2062811295","https://openalex.org/W2070774492","https://openalex.org/W2073795739","https://openalex.org/W2080312287","https://openalex.org/W2093500899","https://openalex.org/W2097074225","https://openalex.org/W2099940712","https://openalex.org/W2101131403","https://openalex.org/W2104599718","https://openalex.org/W2104600947","https://openalex.org/W2104620097","https://openalex.org/W2104974755","https://openalex.org/W2109945199","https://openalex.org/W2110158442","https://openalex.org/W2118273112","https://openalex.org/W2120824855","https://openalex.org/W2121058967","https://openalex.org/W2124438045","https://openalex.org/W2148450250","https://openalex.org/W2149669120","https://openalex.org/W2150066425","https://openalex.org/W2153388956","https://openalex.org/W2164918853","https://openalex.org/W2165015795","https://openalex.org/W2167413693","https://openalex.org/W2534320940","https://openalex.org/W4241716071","https://openalex.org/W6602211262","https://openalex.org/W6635055878","https://openalex.org/W6638194035","https://openalex.org/W6676600194","https://openalex.org/W6678025836","https://openalex.org/W6681850798","https://openalex.org/W7009134754"],"related_works":["https://openalex.org/W2795471480","https://openalex.org/W2104324080","https://openalex.org/W2520322935","https://openalex.org/W3005941135","https://openalex.org/W2086087387","https://openalex.org/W2027589961","https://openalex.org/W2140069086","https://openalex.org/W2155505427","https://openalex.org/W2537394792","https://openalex.org/W2122353381"],"abstract_inverted_index":{"Recently,":[0],"consumer":[1],"depth":[2,22,43,56,74,119],"cameras":[3,27],"have":[4],"gained":[5],"significant":[6],"popularity":[7],"due":[8],"to":[9],"their":[10],"affordable":[11],"cost.":[12],"However,":[13],"the":[14,18,21,41,51,69,72,91,96,107,110,117,147,153,164],"limited":[15,101],"resolution":[16],"and":[17,145,160],"quality":[19],"of":[20,53,71,93,109,155],"map":[23],"generated":[24],"by":[25,60,136],"these":[26],"are":[28,104],"still":[29],"problematic":[30],"for":[31,40],"several":[32],"applications.":[33],"In":[34,48],"this":[35],"paper,":[36],"a":[37,54,61,77,83,122],"novel":[38],"framework":[39],"single":[42,55],"image":[44,57,75,120],"superresolution":[45],"is":[46,58,66],"proposed.":[47],"our":[49,156],"framework,":[50],"upscaling":[52],"guided":[59],"high-resolution":[62,111,118],"edge":[63,97,112],"map,":[64,113],"which":[65],"constructed":[67],"from":[68],"edges":[70],"low-resolution":[73],"through":[76,121],"Markov":[78],"random":[79],"field":[80],"optimization":[81],"in":[82],"patch":[84],"synthesis":[85],"based":[86],"manner.":[87],"We":[88],"also":[89,141],"explore":[90],"self-similarity":[92],"patches":[94],"during":[95],"construction":[98],"stage,":[99],"when":[100],"training":[102],"data":[103],"available.":[105],"With":[106],"guidance":[108,129],"we":[114],"propose":[115],"upsampling":[116],"modified":[123],"joint":[124],"bilateral":[125],"filter.":[126],"The":[127],"edge-based":[128],"not":[130],"only":[131],"helps":[132],"avoiding":[133],"artifacts":[134,144],"introduced":[135],"direct":[137],"texture":[138],"prediction,":[139],"but":[140],"reduces":[142],"jagged":[143],"preserves":[146],"sharp":[148],"edges.":[149],"Experimental":[150],"results":[151],"demonstrate":[152],"effectiveness":[154],"method":[157],"both":[158],"qualitatively":[159],"quantitatively":[161],"compared":[162],"with":[163],"state-of-the-art":[165],"methods.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":25},{"year":2020,"cited_by_count":26},{"year":2019,"cited_by_count":29},{"year":2018,"cited_by_count":28},{"year":2017,"cited_by_count":18},{"year":2016,"cited_by_count":11}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}