{"id":"https://openalex.org/W2789603018","doi":"https://doi.org/10.1145/3162957.3163055","title":"Super-resolution reconstruction of sparse dictionaries based on integrated feature","display_name":"Super-resolution reconstruction of sparse dictionaries based on integrated feature","publication_year":2017,"publication_date":"2017-11-24","ids":{"openalex":"https://openalex.org/W2789603018","doi":"https://doi.org/10.1145/3162957.3163055","mag":"2789603018"},"language":"en","primary_location":{"id":"doi:10.1145/3162957.3163055","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3162957.3163055","pdf_url":null,"source":{"id":"https://openalex.org/S4306523808","display_name":"Proceedings of the 3rd International Conference on Communication and Information Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Communication and Information Processing","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/A5100607929","display_name":"Dan Li","orcid":"https://orcid.org/0000-0002-3656-1358"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Li","raw_affiliation_strings":["Xinjiang University, Urumqi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinjiang University, Urumqi, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081489939","display_name":"Liejun Wang","orcid":"https://orcid.org/0000-0003-0210-2273"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liejun Wang","raw_affiliation_strings":["Xinjiang University, Urumqi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinjiang University, Urumqi, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086121472","display_name":"Jiwei Qin","orcid":"https://orcid.org/0000-0001-7023-2630"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiwei Qin","raw_affiliation_strings":["Xinjiang University, Urumqi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinjiang University, Urumqi, China","institution_ids":["https://openalex.org/I96908189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I96908189"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20454991,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"468","last_page":"473"},"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":0.9984999895095825,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9937000274658203,"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/sparse-approximation","display_name":"Sparse approximation","score":0.7581288814544678},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7202948331832886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7164874076843262},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6373705267906189},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6291353106498718},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.613347589969635},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6101837754249573},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5655021667480469},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5339395403862},{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.5191540122032166},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5040990114212036},{"id":"https://openalex.org/keywords/superresolution","display_name":"Superresolution","score":0.4376336336135864},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4253579080104828},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4036206007003784},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16658028960227966}],"concepts":[{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.7581288814544678},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7202948331832886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7164874076843262},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6373705267906189},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6291353106498718},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.613347589969635},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6101837754249573},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5655021667480469},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5339395403862},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.5191540122032166},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5040990114212036},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.4376336336135864},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4253579080104828},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4036206007003784},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16658028960227966},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3162957.3163055","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3162957.3163055","pdf_url":null,"source":{"id":"https://openalex.org/S4306523808","display_name":"Proceedings of the 3rd International Conference on Communication and Information Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Communication and Information Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W70234347","https://openalex.org/W1791560514","https://openalex.org/W1996356993","https://openalex.org/W2048736270","https://openalex.org/W2056935845","https://openalex.org/W2067100200","https://openalex.org/W2069912449","https://openalex.org/W2118963448","https://openalex.org/W2121058967","https://openalex.org/W2131349449","https://openalex.org/W2133665775","https://openalex.org/W2149669120","https://openalex.org/W2150081556","https://openalex.org/W2160558632","https://openalex.org/W2161516371"],"related_works":["https://openalex.org/W2163296013","https://openalex.org/W2743859443","https://openalex.org/W2326995835","https://openalex.org/W165915117","https://openalex.org/W2059402478","https://openalex.org/W2123347777","https://openalex.org/W4387804363","https://openalex.org/W3004000015","https://openalex.org/W2559771220","https://openalex.org/W4288598071"],"abstract_inverted_index":{"Traditional":[0],"learning-based":[1],"super-resolution":[2],"(SR)":[3],"algorithms":[4,125],"just":[5],"use":[6],"simple":[7],"image":[8,53,65,81,143],"gradient":[9,37],"features":[10],"that":[11,75],"make":[12],"it":[13],"difficult":[14],"to":[15,108,140],"take":[16],"advantage":[17],"of":[18,22,45,61,79,99],"the":[19,33,42,59,76,93,96,100,104,127,136,142],"prior":[20],"information":[21,107],"training":[23,44],"samples.":[24],"This":[25],"paper":[26],"proposes":[27],"an":[28],"integrated":[29],"feature":[30],"which":[31],"combination":[32],"improved":[34],"first-order,":[35],"second-order":[36],"and":[38,49,63,83,120,129,132,144],"median":[39],"features.":[40],"Through":[41],"joint":[43],"high":[46],"resolution":[47,51],"(HR)":[48],"low":[50],"(LR)":[52],"block":[54],"dictionaries,":[55],"we":[56,117,133],"can":[57,90,134],"strengthen":[58],"similarity":[60],"HR":[62,84],"LR":[64,80],"blocks":[66,82],"with":[67],"their":[68],"corresponding":[69],"real":[70],"dictionary":[71,86],"sparse":[72,77],"representation,":[73],"so":[74],"representation":[78],"over-complete":[85],"work":[87],"together.":[88],"It":[89],"better":[91],"grasp":[92],"connection":[94],"between":[95],"high-frequency":[97],"components":[98],"image,":[101],"while":[102],"retaining":[103],"useful":[105],"low-frequency":[106],"obtain":[109],"a":[110],"more":[111],"accurate":[112],"prediction.":[113],"In":[114],"this":[115],"paper,":[116],"get":[118],"PSNR":[119],"SSIM":[121],"higher":[122],"than":[123],"other":[124],"on":[126],"Yang":[128],"Set5":[130],"datasets,":[131],"see":[135],"prominent":[137],"edge":[138,146],"detail":[139],"keep":[141],"clear":[145],"information.":[147]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}