{"id":"https://openalex.org/W2962717947","doi":"https://doi.org/10.1109/tip.2017.2768185","title":"How Does the Low-Rank Matrix Decomposition Help Internal and External Learnings for Super-Resolution","display_name":"How Does the Low-Rank Matrix Decomposition Help Internal and External Learnings for Super-Resolution","publication_year":2017,"publication_date":"2017-10-30","ids":{"openalex":"https://openalex.org/W2962717947","doi":"https://doi.org/10.1109/tip.2017.2768185","mag":"2962717947","pmid":"https://pubmed.ncbi.nlm.nih.gov/29220313"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2017.2768185","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2017.2768185","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/A5065660222","display_name":"Shuang Wang","orcid":"https://orcid.org/0000-0003-4940-1211"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuang Wang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Institute of Intelligent Image Processing, International Research Center for Intelligent Perception and Computation, Xidian University, Xi\u2019an, China","Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Institute of Intelligent Image Processing, International Research Center for Intelligent Perception and Computation, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Institute of Intelligent Image Processing, International Research Center for Intelligent Perception and Computation, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Institute of Intelligent Image Processing, International Research Center for Intelligent Perception and Computation, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110377179","display_name":"Bo Yue","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Yue","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Institute of Intelligent Image Processing, International Research Center for Intelligent Perception and Computation, Xidian University, Xi\u2019an, China","Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Institute of Intelligent Image Processing, International Research Center for Intelligent Perception and Computation, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Institute of Intelligent Image Processing, International Research Center for Intelligent Perception and Computation, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Institute of Intelligent Image Processing, International Research Center for Intelligent Perception and Computation, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083213551","display_name":"Xuefeng Liang","orcid":"https://orcid.org/0000-0002-1448-0477"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xuefeng Liang","raw_affiliation_strings":["Department of Intelligence Science and Technology, Kyoto University, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Intelligence Science and Technology, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050630882","display_name":"Licheng Jiao","orcid":"https://orcid.org/0000-0003-3354-9617"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Licheng Jiao","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Institute of Intelligent Image Processing, International Research Center for Intelligent Perception and Computation, Xidian University, Xi\u2019an, China","Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Institute of Intelligent Image Processing, International Research Center for Intelligent Perception and Computation, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Institute of Intelligent Image Processing, International Research Center for Intelligent Perception and Computation, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Institute of Intelligent Image Processing, International Research Center for Intelligent Perception and Computation, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5065660222"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.6372,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.79480233,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"27","issue":"3","first_page":"1086","last_page":"1099"},"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/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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/matrix-decomposition","display_name":"Matrix decomposition","score":0.570730447769165},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.47150081396102905},{"id":"https://openalex.org/keywords/matrix-algebra","display_name":"Matrix algebra","score":0.4390898048877716},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.4232422113418579},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42101380228996277},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4168710708618164},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4036247134208679},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37975144386291504},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36398816108703613},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13543719053268433},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.11483660340309143},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.1060735285282135}],"concepts":[{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.570730447769165},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.47150081396102905},{"id":"https://openalex.org/C2988995629","wikidata":"https://www.wikidata.org/wiki/Q2915729","display_name":"Matrix algebra","level":3,"score":0.4390898048877716},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4232422113418579},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42101380228996277},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4168710708618164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4036247134208679},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37975144386291504},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36398816108703613},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13543719053268433},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.11483660340309143},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.1060735285282135},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2017.2768185","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2017.2768185","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:29220313","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29220313","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W135113724","https://openalex.org/W935139217","https://openalex.org/W1201875361","https://openalex.org/W1791560514","https://openalex.org/W1806901794","https://openalex.org/W1897123318","https://openalex.org/W1930824406","https://openalex.org/W1949096787","https://openalex.org/W1976416062","https://openalex.org/W1994040806","https://openalex.org/W1995258445","https://openalex.org/W2000355138","https://openalex.org/W2003753589","https://openalex.org/W2011952414","https://openalex.org/W2013015287","https://openalex.org/W2014311222","https://openalex.org/W2047071281","https://openalex.org/W2047920195","https://openalex.org/W2056370875","https://openalex.org/W2057126662","https://openalex.org/W2079361630","https://openalex.org/W2087436818","https://openalex.org/W2088254198","https://openalex.org/W2097073572","https://openalex.org/W2097074225","https://openalex.org/W2097622337","https://openalex.org/W2100556411","https://openalex.org/W2118103795","https://openalex.org/W2120824855","https://openalex.org/W2121058967","https://openalex.org/W2121927366","https://openalex.org/W2134332047","https://openalex.org/W2137290314","https://openalex.org/W2142077116","https://openalex.org/W2145962650","https://openalex.org/W2150081556","https://openalex.org/W2154872931","https://openalex.org/W2161516371","https://openalex.org/W2187061624","https://openalex.org/W2242218935","https://openalex.org/W2263468737","https://openalex.org/W2265701153","https://openalex.org/W2345557152","https://openalex.org/W2503339013","https://openalex.org/W2534320940","https://openalex.org/W2567804583","https://openalex.org/W3104624268","https://openalex.org/W3105700508","https://openalex.org/W4377561911","https://openalex.org/W6602211262","https://openalex.org/W6624640001","https://openalex.org/W6653944615","https://openalex.org/W6677645113","https://openalex.org/W6678025836","https://openalex.org/W6681016373","https://openalex.org/W6682644385","https://openalex.org/W6683660953","https://openalex.org/W6686960354","https://openalex.org/W6724673846"],"related_works":["https://openalex.org/W2380059383","https://openalex.org/W2063679720","https://openalex.org/W2067481825","https://openalex.org/W2075046161","https://openalex.org/W2185495545","https://openalex.org/W2547083368","https://openalex.org/W2031856784","https://openalex.org/W2510721029","https://openalex.org/W2385335131","https://openalex.org/W239705756"],"abstract_inverted_index":{"Wisely":[0],"utilizing":[1],"the":[2,21,51,78,83,101,112,117,124,129,133],"internal":[3,79],"and":[4,26,42,45,68,82,97,114,140,152],"external":[5,84],"learning":[6,66,80,85,121,135],"methods":[7,67,122],"is":[8],"a":[9,59,71],"new":[10],"challenge":[11],"in":[12,38,50,137],"super-resolution":[13],"problem.":[14],"To":[15,74],"address":[16],"this":[17,76],"issue,":[18],"we":[19],"analyze":[20],"attributes":[22],"of":[23,30,119],"two":[24,28,65,120],"methodologies":[25],"find":[27],"observations":[29],"their":[31],"recovered":[32],"details:":[33],"1)":[34],"they":[35,47],"are":[36,87],"complementary":[37],"both":[39,138],"feature":[40],"space":[41],"image":[43],"plane":[44],"2)":[46],"distribute":[48],"sparsely":[49],"spatial":[52],"space.":[53],"These":[54],"inspire":[55],"us":[56],"to":[57,89,110],"propose":[58],"low-rank":[60,103],"solution":[61,104,131],"which":[62],"effectively":[63],"integrates":[64],"then":[69],"achieves":[70],"superior":[72,147],"result.":[73],"fit":[75],"solution,":[77],"method":[81,86,136],"tailored":[88],"produce":[90],"multiple":[91],"preliminary":[92],"results.":[93],"Our":[94],"theoretical":[95],"analysis":[96],"experiment":[98],"prove":[99],"that":[100],"proposed":[102,130],"does":[105],"not":[106],"require":[107],"massive":[108],"inputs":[109],"guarantee":[111],"performance,":[113],"thereby":[115],"simplifying":[116],"design":[118],"for":[123],"solution.":[125],"Intensive":[126],"experiments":[127],"show":[128],"improves":[132],"single":[134],"qualitative":[139],"quantitative":[141],"assessments.":[142],"Surprisingly,":[143],"it":[144],"shows":[145],"more":[146],"capability":[148],"on":[149],"noisy":[150],"images":[151],"outperforms":[153],"state-of-the-art":[154],"methods.":[155]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
