{"id":"https://openalex.org/W2058931101","doi":"https://doi.org/10.1109/icip.2014.7025429","title":"Example-based super-resolution using self-patches and approximated constrained least squares filter","display_name":"Example-based super-resolution using self-patches and approximated constrained least squares filter","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2058931101","doi":"https://doi.org/10.1109/icip.2014.7025429","mag":"2058931101"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2014.7025429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2014.7025429","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 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/A5022036251","display_name":"Changhun Cho","orcid":null},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Changhun Cho","raw_affiliation_strings":["Multimedia, and Film Seoul, Chung-Ang University, Korea","Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film Seoul, Chung-Ang University, Korea"],"affiliations":[{"raw_affiliation_string":"Multimedia, and Film Seoul, Chung-Ang University, Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film Seoul, Chung-Ang University, Korea","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108088376","display_name":"Jaehwan Jeon","orcid":null},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaehwan Jeon","raw_affiliation_strings":["Multimedia, and Film Seoul, Chung-Ang University, Korea","Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film Seoul, Chung-Ang University, Korea"],"affiliations":[{"raw_affiliation_string":"Multimedia, and Film Seoul, Chung-Ang University, Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film Seoul, Chung-Ang University, Korea","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013926864","display_name":"Joonki Paik","orcid":"https://orcid.org/0000-0002-8593-7155"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Joonki Paik","raw_affiliation_strings":["Multimedia, and Film Seoul, Chung-Ang University, Korea","Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film Seoul, Chung-Ang University, Korea"],"affiliations":[{"raw_affiliation_string":"Multimedia, and Film Seoul, Chung-Ang University, Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film Seoul, Chung-Ang University, Korea","institution_ids":["https://openalex.org/I67900169"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5022036251"],"corresponding_institution_ids":["https://openalex.org/I67900169"],"apc_list":null,"apc_paid":null,"fwci":0.9755,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.8025519,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"30","issue":null,"first_page":"2140","last_page":"2144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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":0.9948999881744385,"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"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9901999831199646,"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/peak-signal-to-noise-ratio","display_name":"Peak signal-to-noise ratio","score":0.6368215084075928},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.578782320022583},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5664382576942444},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5341445803642273},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5092207193374634},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.49175503849983215},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.47825658321380615},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.47739237546920776},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.459606409072876},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.4515893757343292},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4468221068382263},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4427814483642578},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.418935090303421},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4163789749145508},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36113041639328003},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3248094618320465},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.27199792861938477},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.07861411571502686}],"concepts":[{"id":"https://openalex.org/C154579607","wikidata":"https://www.wikidata.org/wiki/Q3373850","display_name":"Peak signal-to-noise ratio","level":3,"score":0.6368215084075928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.578782320022583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5664382576942444},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5341445803642273},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5092207193374634},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.49175503849983215},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.47825658321380615},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.47739237546920776},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.459606409072876},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.4515893757343292},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4468221068382263},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4427814483642578},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.418935090303421},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4163789749145508},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36113041639328003},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3248094618320465},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27199792861938477},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.07861411571502686},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2014.7025429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2014.7025429","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1976416062","https://openalex.org/W2045443820","https://openalex.org/W2073484902","https://openalex.org/W2097074225","https://openalex.org/W2113524221","https://openalex.org/W2117317262","https://openalex.org/W2121058967","https://openalex.org/W2165939075","https://openalex.org/W2534320940"],"related_works":["https://openalex.org/W2357322570","https://openalex.org/W2997591215","https://openalex.org/W2227541280","https://openalex.org/W2375480909","https://openalex.org/W2353314428","https://openalex.org/W2012019886","https://openalex.org/W2166090428","https://openalex.org/W2381021552","https://openalex.org/W2354749003","https://openalex.org/W2045818635"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,61],"novel":[4],"super-resolution":[5],"(SR)":[6],"algorithm":[7,13,96],"using":[8,24,34],"local":[9],"self-examples.":[10],"The":[11,68,108],"proposed":[12,69,94,109],"consists":[14],"of":[15,20,30,39,46,64],"three":[16],"steps:":[17],"i)":[18],"generation":[19],"the":[21,31,35,40,47,54,80,93],"patch":[22],"dictionary":[23,84],"multiple-step":[25,87],"image":[26,41],"blurring,":[27],"ii)":[28],"search":[29],"optimum":[32],"patches":[33,51,77],"magnitude":[36],"and":[37,43,49,118,126],"orientation":[38],"gradient,":[42],"iii)":[44],"combination":[45],"restored":[48],"original":[50],"for":[52],"reducing":[53],"patch-mismatching":[55],"error.":[56],"Example-based":[57],"SR":[58,95,110],"methods":[59],"have":[60],"common":[62],"disadvantage":[63],"unnaturally":[65],"reconstructed":[66],"edges.":[67],"method":[70,111],"can":[71],"reconstruct":[72],"realistic":[73],"images":[74,100],"by":[75,86],"searching":[76],"based":[78],"on":[79],"edge":[81],"strength":[82],"in":[83,115],"made":[85],"degradations.":[88],"Experimental":[89],"results":[90],"show":[91],"that":[92],"provides":[97,112],"more":[98],"natural":[99],"with":[101],"less":[102],"synthetic":[103],"artifacts":[104],"than":[105],"existing":[106],"methods.":[107],"significant":[113],"improvement":[114],"both":[116],"subjective":[117],"objective":[119],"measures":[120],"including":[121],"peak-to-peak":[122],"signal-to-noise":[123],"ratio":[124],"(PSNR)":[125],"structural":[127],"similarity":[128],"measure":[129],"(SSIM).":[130]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
