{"id":"https://openalex.org/W2041513428","doi":"https://doi.org/10.1117/12.2002829","title":"Fast texture and structure image reconstruction using the perceptual hash","display_name":"Fast texture and structure image reconstruction using the perceptual hash","publication_year":2013,"publication_date":"2013-02-19","ids":{"openalex":"https://openalex.org/W2041513428","doi":"https://doi.org/10.1117/12.2002829","mag":"2041513428"},"language":"en","primary_location":{"id":"doi:10.1117/12.2002829","doi":"https://doi.org/10.1117/12.2002829","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2002829","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5076403380","display_name":"Viacheslav Voronin","orcid":"https://orcid.org/0000-0001-8114-6383","observed_orcids":["https://orcid.org/0000-0001-8114-6383"]},"institutions":[{"id":"https://openalex.org/I4210097717","display_name":"Don State Technical University","ror":"https://ror.org/00x5je630","country_code":"RU","type":"education","lineage":["https://openalex.org/I4210097717"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"V. V. Voronin","raw_affiliation_strings":["Don State Technical Univ. (Russian Federation)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Don State Technical Univ. (Russian Federation)","institution_ids":["https://openalex.org/I4210097717"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102981113","display_name":"\u0412. \u0418. \u041c\u0430\u0440\u0447\u0443\u043a","orcid":"https://orcid.org/0000-0001-8576-0081","observed_orcids":["https://orcid.org/0000-0001-8576-0081"]},"institutions":[{"id":"https://openalex.org/I4210097717","display_name":"Don State Technical University","ror":"https://ror.org/00x5je630","country_code":"RU","type":"education","lineage":["https://openalex.org/I4210097717"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"V. I. Marchuk","raw_affiliation_strings":["Don State Technical Univ. (Russian Federation)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Don State Technical Univ. (Russian Federation)","institution_ids":["https://openalex.org/I4210097717"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016907914","display_name":"V. A. Frantc","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210097717","display_name":"Don State Technical University","ror":"https://ror.org/00x5je630","country_code":"RU","type":"education","lineage":["https://openalex.org/I4210097717"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"V. A. Frantc","raw_affiliation_strings":["Don State Technical Univ. (Russian Federation)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Don State Technical Univ. (Russian Federation)","institution_ids":["https://openalex.org/I4210097717"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090213299","display_name":"Karen Egiazarian","orcid":"https://orcid.org/0000-0002-8135-1085","observed_orcids":["https://orcid.org/0000-0002-8135-1085"]},"institutions":[{"id":"https://openalex.org/I4387152565","display_name":"Tampere University of Technology","ror":"https://ror.org/02ba3pt07","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849","https://openalex.org/I4387152565"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Karen Egiazarian","raw_affiliation_strings":["Tampere Univ. of Technology (Finland)","Tampere University of Technology, , Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tampere Univ. of Technology (Finland)","institution_ids":["https://openalex.org/I4387152565"]},{"raw_affiliation_string":"Tampere University of Technology, , Finland","institution_ids":["https://openalex.org/I4387152565"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6326,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.64456593,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":"8655","issue":null,"first_page":"86550R","last_page":"86550R"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.7865999937057495,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.7865999937057495,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.07580000162124634,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.041999999433755875,"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/image-inpainting","display_name":"image inpainting","score":0.9950000047683716},{"id":"https://openalex.org/keywords/image-reconstruction","display_name":"image reconstruction","score":0.652999997138977},{"id":"https://openalex.org/keywords/perceptual-hash","display_name":"perceptual hash","score":0.9430000185966492},{"id":"https://openalex.org/keywords/texture-reconstruction","display_name":"texture reconstruction","score":0.6539999842643738},{"id":"https://openalex.org/keywords/structure-reconstruction","display_name":"structure reconstruction","score":0.6970000267028809},{"id":"https://openalex.org/keywords/cubic-spline-curves","display_name":"cubic spline curves","score":0.4399999976158142},{"id":"https://openalex.org/keywords/fast-marching-method","display_name":"fast marching method","score":0.7730000019073486},{"id":"https://openalex.org/keywords/exemplar-based-inpainting","display_name":"exemplar-based inpainting","score":0.8560000061988831}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8212659358978271},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.8026041984558105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.775581419467926},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7325602769851685},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6541155576705933},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.5956200361251831},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48012757301330566},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47322049736976624},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.42879530787467957},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2002829","doi":"https://doi.org/10.1117/12.2002829","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2002829","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2024734272","https://openalex.org/W2310980473","https://openalex.org/W1993175165","https://openalex.org/W2759008232","https://openalex.org/W2001070267","https://openalex.org/W2034296936","https://openalex.org/W2355346932","https://openalex.org/W92349337","https://openalex.org/W2116089221","https://openalex.org/W1994786405"],"abstract_inverted_index":{"This":[0,150],"paper":[1],"focuses":[2],"on":[3,36,113,171,205],"the":[4,27,32,37,55,79,85,94,104,114,117,132,145,155,159,164,183,188],"fast":[5,95],"texture":[6],"and":[7,72,76,180,202],"structure":[8,71,143],"reconstruction":[9,198],"of":[10,19,31,84,103,116,147,163,174,199],"images.":[11,207],"The":[12,22,40,82,98,166],"proposed":[13,167,189],"method,":[14],"applied":[15,67],"to":[16,53,68,73,88,126,139,153,158,193],"images,":[17,175],"consists":[18],"several":[20],"steps.":[21],"first":[23],"one":[24],"deals":[25],"with":[26,176,182],"extracted":[28],"textural":[29],"features":[30,179],"input":[33],"images":[34],"based":[35,106],"Law\u2019s":[38],"energy.":[39],"pixels":[41,58],"around":[42],"damaged":[43,80],"image":[44,185],"regions":[45,118],"are":[46,108],"clustered":[47],"using":[48,93],"these":[49],"features,":[50],"that":[51],"allow":[52],"define":[54],"correspondence":[56],"between":[57],"from":[59],"different":[60,177],"patches.":[61,149],"Second,":[62],"cubic":[63],"spline":[64],"curve":[65],"is":[66,91,122,169,191],"reconstruct":[69],"a":[70,136],"connect":[74],"edges":[75],"contours":[77],"in":[78,197],"area.":[81],"choice":[83],"current":[86],"pixel":[87,121],"be":[89],"recovered":[90],"decided":[92],"marching":[96],"approach.":[97],"Telea":[99],"method":[100,107,168],"or":[101],"modifications":[102],"exemplar":[105],"used":[109],"after":[110],"this":[111],"depending":[112],"classification":[115],"where":[119],"to-be-restored":[120],"located.":[123],"In":[124],"modification":[125],"quickly":[127],"find":[128],"patches":[129],"we":[130],"use":[131],"perceptual":[133],"hash.":[134],"Such":[135],"strategy":[137],"allows":[138],"get":[140],"some":[141],"data":[142],"containing":[144],"hashes":[146],"similar":[148],"enables":[151],"us":[152],"reduce":[154],"search":[156],"procedure":[157,160],"for":[161],"\"calculations\"":[162],"patch.":[165],"tested":[170],"various":[172],"samples":[173],"geometrical":[178],"compared":[181],"state-of-the-art":[184],"inpainting":[186],"methods;":[187],"technique":[190],"shown":[192],"produce":[194],"better":[195],"results":[196],"missing":[200],"small":[201],"large":[203],"objects":[204],"test":[206]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}
