{"id":"https://openalex.org/W2112391032","doi":"https://doi.org/10.1109/cvpr.2010.5540214","title":"A content-aware image prior","display_name":"A content-aware image prior","publication_year":2010,"publication_date":"2010-06-01","ids":{"openalex":"https://openalex.org/W2112391032","doi":"https://doi.org/10.1109/cvpr.2010.5540214","mag":"2112391032"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2010.5540214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5540214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/1721.1/71890","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043036200","display_name":"Taeg Sang Cho","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Taeg Sang Cho","raw_affiliation_strings":["Massachusetts Institute of Technology, USA","Massachusetts Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]},{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072006037","display_name":"Neel Joshi","orcid":"https://orcid.org/0000-0001-8236-3566"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neel Joshi","raw_affiliation_strings":["Microsoft Research Limited, USA","Microsoft research#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Limited, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft research#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058450549","display_name":"C. Lawrence Zitnick","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"C. Lawrence Zitnick","raw_affiliation_strings":["Microsoft Research Limited, USA","Microsoft research#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Limited, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft research#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004671096","display_name":"Sing Bing Kang","orcid":"https://orcid.org/0000-0003-2016-2915"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sing Bing Kang","raw_affiliation_strings":["Microsoft Research Limited, USA","Microsoft research#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Limited, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft research#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077002817","display_name":"Richard Szeliski","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Richard Szeliski","raw_affiliation_strings":["Microsoft Research Limited, USA","Microsoft research#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Limited, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft research#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074429265","display_name":"William T. Freeman","orcid":"https://orcid.org/0000-0002-2231-7995"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William T. Freeman","raw_affiliation_strings":["Massachusetts Institute of Technology, USA","Massachusetts Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, USA","institution_ids":["https://openalex.org/I63966007"]},{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5043036200"],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":10.668,"has_fulltext":false,"cited_by_count":99,"citation_normalized_percentile":{"value":0.98719548,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"169","last_page":"176"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9990000128746033,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9990000128746033,"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":0.9987000226974487,"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":0.9943000078201294,"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/image-restoration","display_name":"Image restoration","score":0.744561493396759},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6967693567276001},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.63579261302948},{"id":"https://openalex.org/keywords/deconvolution","display_name":"Deconvolution","score":0.5921869277954102},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.5742651224136353},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5451157093048096},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.524389922618866},{"id":"https://openalex.org/keywords/image-gradient","display_name":"Image gradient","score":0.46621543169021606},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4636244773864746},{"id":"https://openalex.org/keywords/ringing-artifacts","display_name":"Ringing artifacts","score":0.46054619550704956},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.44263648986816406},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.44114676117897034},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4357556700706482},{"id":"https://openalex.org/keywords/ringing","display_name":"Ringing","score":0.4200698137283325},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.4101142883300781},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3668592870235443},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.35155540704727173},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2888360321521759},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18282797932624817},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.09113156795501709}],"concepts":[{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.744561493396759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6967693567276001},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.63579261302948},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.5921869277954102},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.5742651224136353},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5451157093048096},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.524389922618866},{"id":"https://openalex.org/C182037307","wikidata":"https://www.wikidata.org/wiki/Q17039097","display_name":"Image gradient","level":5,"score":0.46621543169021606},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4636244773864746},{"id":"https://openalex.org/C17828673","wikidata":"https://www.wikidata.org/wiki/Q7334899","display_name":"Ringing artifacts","level":3,"score":0.46054619550704956},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.44263648986816406},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.44114676117897034},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4357556700706482},{"id":"https://openalex.org/C30684385","wikidata":"https://www.wikidata.org/wiki/Q176509","display_name":"Ringing","level":3,"score":0.4200698137283325},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.4101142883300781},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3668592870235443},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.35155540704727173},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2888360321521759},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18282797932624817},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.09113156795501709},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/cvpr.2010.5540214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5540214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.176.86","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.176.86","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ai.mit.edu/people/wtf/papers/ContentAwarePriorCVPR2010.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.192.792","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.192.792","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/%7Elarryz/ContentAwarePrior_CVPR2010.pdf","raw_type":"text"},{"id":"pmh:oai:dspace.mit.edu:1721.1/71890","is_oa":true,"landing_page_url":"http://hdl.handle.net/1721.1/71890","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE","raw_type":"http://purl.org/eprint/type/ConferencePaper"}],"best_oa_location":{"id":"pmh:oai:dspace.mit.edu:1721.1/71890","is_oa":true,"landing_page_url":"http://hdl.handle.net/1721.1/71890","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE","raw_type":"http://purl.org/eprint/type/ConferencePaper"},"sustainable_development_goals":[{"score":0.6200000047683716,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332195","display_name":"Samsung","ror":"https://ror.org/04w3jy968"},{"id":"https://openalex.org/F4320333591","display_name":"Multidisciplinary University Research Initiative","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1485280399","https://openalex.org/W1593939129","https://openalex.org/W1829102423","https://openalex.org/W1991605728","https://openalex.org/W2001002651","https://openalex.org/W2010016312","https://openalex.org/W2024991751","https://openalex.org/W2064594480","https://openalex.org/W2097713019","https://openalex.org/W2098535678","https://openalex.org/W2099244020","https://openalex.org/W2109991658","https://openalex.org/W2110764733","https://openalex.org/W2117853853","https://openalex.org/W2119938170","https://openalex.org/W2120853285","https://openalex.org/W2122952014","https://openalex.org/W2126247504","https://openalex.org/W2127847374","https://openalex.org/W2131686571","https://openalex.org/W2133071149","https://openalex.org/W2133665775","https://openalex.org/W2138448681","https://openalex.org/W2149925139","https://openalex.org/W2150920547","https://openalex.org/W2153635508","https://openalex.org/W2154571593","https://openalex.org/W2160547390","https://openalex.org/W2160715448","https://openalex.org/W2167053624","https://openalex.org/W2168896212","https://openalex.org/W3120421331","https://openalex.org/W4206519171","https://openalex.org/W4247043502","https://openalex.org/W6677760137","https://openalex.org/W6678179167","https://openalex.org/W6680414531","https://openalex.org/W6683488002"],"related_works":["https://openalex.org/W2104708016","https://openalex.org/W2390701595","https://openalex.org/W2090956370","https://openalex.org/W1542850441","https://openalex.org/W2293401449","https://openalex.org/W2095868395","https://openalex.org/W2528053022","https://openalex.org/W2163761581","https://openalex.org/W2018815104","https://openalex.org/W2566126253"],"abstract_inverted_index":{"In":[0],"image":[1,17,20,34,69,107,113],"restoration":[2,21,108],"tasks,":[3],"a":[4,24,83],"heavy-tailed":[5],"gradient":[6,26,42,72,98],"distribution":[7],"of":[8],"natural":[9],"images":[10],"has":[11],"been":[12],"extensively":[13],"exploited":[14],"as":[15,78,128,130],"an":[16,33,67,106],"prior.":[18,70,99],"Most":[19],"algorithms":[22],"impose":[23],"sparse":[25,41,97],"prior":[27,43,114,122],"on":[28,140],"the":[29,40,57,96,112,116,121],"whole":[30],"image,":[31],"reconstructing":[32],"with":[35],"piecewise":[36],"smooth":[37],"characteristics.":[38,133],"While":[39],"removes":[44],"ringing":[45],"and":[46,86,142],"noise":[47],"artifacts,":[48],"it":[49],"also":[50],"tends":[51],"to":[52,65,82,115,123],"remove":[53],"mid-frequency":[54],"textures,":[55,76],"degrading":[56],"visual":[58,136],"quality.":[59],"We":[60,119],"can":[61],"attribute":[62],"such":[63,77,90],"degradations":[64],"imposing":[66],"incorrect":[68],"The":[71],"profile":[73],"in":[74,135],"fractal-like":[75],"trees,":[79],"is":[80,138],"close":[81],"Gaussian":[84],"distribution,":[85],"small":[87],"gradients":[88],"from":[89],"regions":[91],"are":[92],"severely":[93],"penalized":[94],"by":[95],"To":[100],"address":[101],"this":[102],"issue,":[103],"we":[104],"introduce":[105],"algorithm":[109],"that":[110],"adapts":[111],"underlying":[117],"texture.":[118],"adapt":[120],"both":[124],"low-level":[125],"local":[126],"structures":[127],"well":[129],"mid-level":[131],"textural":[132],"Improvements":[134],"quality":[137],"demonstrated":[139],"deconvolution":[141],"denoising":[143],"tasks.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":16},{"year":2014,"cited_by_count":13},{"year":2013,"cited_by_count":14},{"year":2012,"cited_by_count":10}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
