{"id":"https://openalex.org/W2010134957","doi":"https://doi.org/10.1109/icip.2014.7025798","title":"A confidence growing model for super-resolution","display_name":"A confidence growing model for super-resolution","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2010134957","doi":"https://doi.org/10.1109/icip.2014.7025798","mag":"2010134957"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2014.7025798","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2014.7025798","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":"conference-paper","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/A5084268991","display_name":"Sina Lin","orcid":"https://orcid.org/0009-0008-7837-5925"},"institutions":[{"id":"https://openalex.org/I1295929820","display_name":"Yamaha (Japan)","ror":"https://ror.org/05s7fvh27","country_code":"JP","type":"company","lineage":["https://openalex.org/I1295929820"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN","JP"],"is_corresponding":false,"raw_author_name":"Sina Lin","raw_affiliation_strings":["Intelligent Computing and Machine Leaning Lab, Beihang University, Beijing, China","Yamaha Corporation, Hamamatsu, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Computing and Machine Leaning Lab, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Yamaha Corporation, Hamamatsu, Japan","institution_ids":["https://openalex.org/I1295929820"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032405950","display_name":"Zengchang Qin","orcid":"https://orcid.org/0000-0002-8084-6721"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zengchang Qin","raw_affiliation_strings":["Intelligent Computing and Machine Leaning Lab, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Computing and Machine Leaning Lab, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048686150","display_name":"Renjie Liao","orcid":"https://orcid.org/0009-0001-1660-9959"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Renjie Liao","raw_affiliation_strings":["Department of CSE, Chinese University of Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of CSE, Chinese University of Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041005536","display_name":"Tao Wan","orcid":"https://orcid.org/0000-0002-2962-4066"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Wan","raw_affiliation_strings":["School of Biological Science and Medical Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Biological Science and Medical Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09683949,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":null,"first_page":"3929","last_page":"3933"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9962999820709229,"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":0.9959999918937683,"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/computer-science","display_name":"Computer science","score":0.6993169784545898},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6925097703933716},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5982170701026917},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5804558396339417},{"id":"https://openalex.org/keywords/raster-graphics","display_name":"Raster graphics","score":0.5788355469703674},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5650573372840881},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5628343224525452},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.5442940592765808},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5357605218887329},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.527545690536499},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5270215272903442},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4386931359767914},{"id":"https://openalex.org/keywords/superresolution","display_name":"Superresolution","score":0.4382777512073517},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4340527057647705},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40086159110069275},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18690821528434753},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07339182496070862},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.06538298726081848}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6993169784545898},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6925097703933716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5982170701026917},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5804558396339417},{"id":"https://openalex.org/C181844469","wikidata":"https://www.wikidata.org/wiki/Q182270","display_name":"Raster graphics","level":2,"score":0.5788355469703674},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5650573372840881},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5628343224525452},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.5442940592765808},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5357605218887329},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.527545690536499},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5270215272903442},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4386931359767914},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.4382777512073517},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4340527057647705},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40086159110069275},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18690821528434753},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07339182496070862},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.06538298726081848},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2014.7025798","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2014.7025798","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":22,"referenced_works":["https://openalex.org/W1967441049","https://openalex.org/W1998500702","https://openalex.org/W2044011870","https://openalex.org/W2061398022","https://openalex.org/W2081385919","https://openalex.org/W2097074225","https://openalex.org/W2107306730","https://openalex.org/W2107384509","https://openalex.org/W2121927366","https://openalex.org/W2130103520","https://openalex.org/W2133665775","https://openalex.org/W2149760002","https://openalex.org/W2163935418","https://openalex.org/W2164551808","https://openalex.org/W2165939075","https://openalex.org/W2534320940","https://openalex.org/W3040777582","https://openalex.org/W3137074406","https://openalex.org/W6642029968","https://openalex.org/W6679388247","https://openalex.org/W6683680428","https://openalex.org/W6780413204"],"related_works":["https://openalex.org/W2093392189","https://openalex.org/W2393022482","https://openalex.org/W2377346130","https://openalex.org/W2743147667","https://openalex.org/W2361092061","https://openalex.org/W2773877060","https://openalex.org/W1587389446","https://openalex.org/W3004000015","https://openalex.org/W2559771220","https://openalex.org/W4387300017"],"abstract_inverted_index":{"Single":[0],"image":[1,10,23,45],"super-resolution":[2],"(SR)":[3],"aims":[4],"at":[5],"generating":[6],"a":[7,27,47,59,73,86,105],"high-resolution":[8,44],"(HR)":[9],"from":[11],"one":[12],"low-resolution":[13],"(LR)":[14],"input.":[15],"In":[16],"this":[17,97],"paper,":[18],"we":[19],"focus":[20],"on":[21,32,104],"single":[22],"SR":[24,109],"by":[25,71],"using":[26,58],"confidence":[28,61],"growing":[29],"model":[30],"based":[31],"an":[33],"example-based":[34],"super":[35],"resolution":[36],"approach.":[37],"Compared":[38],"to":[39,68,84,89],"previous":[40],"works":[41],"that":[42,96],"reconstruct":[43],"in":[46,76],"raster":[48],"scan":[49],"order,":[50],"the":[51,56,106],"new":[52,60],"proposed":[53],"method":[54,99],"reconstructs":[55],"patches":[57],"measure.":[62],"More":[63],"confident":[64],"reconstructions":[65],"are":[66],"propagated":[67],"neighboring":[69],"areas":[70],"enforcing":[72],"smoothness":[74],"constraint":[75],"selecting":[77],"patches.":[78],"We":[79],"also":[80],"adopt":[81],"hierarchical":[82],"clustering":[83],"construct":[85],"training":[87],"set":[88],"speed":[90],"up":[91],"processing.":[92],"Experimental":[93],"results":[94],"demonstrate":[95],"simple":[98],"outperforms":[100],"existing":[101],"state-of-the-art":[102],"algorithms":[103],"given":[107],"benchmark":[108],"test":[110],"images.":[111]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
