{"id":"https://openalex.org/W2791943814","doi":"https://doi.org/10.1109/icip.2017.8296653","title":"MF-LRTC: Multi-filters guided low-rank tensor coding for image restoration","display_name":"MF-LRTC: Multi-filters guided low-rank tensor coding for image restoration","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2791943814","doi":"https://doi.org/10.1109/icip.2017.8296653","mag":"2791943814"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296653","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296653","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5029231471","display_name":"Hongyang Lu","orcid":"https://orcid.org/0000-0002-4077-6802"},"institutions":[{"id":"https://openalex.org/I141649914","display_name":"Nanchang University","ror":"https://ror.org/042v6xz23","country_code":"CN","type":"education","lineage":["https://openalex.org/I141649914"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyang Lu","raw_affiliation_strings":["Department of Electronic Information Engineering, Nanchang University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Information Engineering, Nanchang University, Nanchang, China","institution_ids":["https://openalex.org/I141649914"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030175144","display_name":"Sanqian Li","orcid":null},"institutions":[{"id":"https://openalex.org/I141649914","display_name":"Nanchang University","ror":"https://ror.org/042v6xz23","country_code":"CN","type":"education","lineage":["https://openalex.org/I141649914"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sanqian Li","raw_affiliation_strings":["Department of Electronic Information Engineering, Nanchang University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Information Engineering, Nanchang University, Nanchang, China","institution_ids":["https://openalex.org/I141649914"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057647276","display_name":"Qiegen Liu","orcid":"https://orcid.org/0000-0003-4717-2283"},"institutions":[{"id":"https://openalex.org/I141649914","display_name":"Nanchang University","ror":"https://ror.org/042v6xz23","country_code":"CN","type":"education","lineage":["https://openalex.org/I141649914"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiegen Liu","raw_affiliation_strings":["Department of Electronic Information Engineering, Nanchang University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Information Engineering, Nanchang University, Nanchang, China","institution_ids":["https://openalex.org/I141649914"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100370103","display_name":"Yuhao Wang","orcid":"https://orcid.org/0000-0002-8445-0361"},"institutions":[{"id":"https://openalex.org/I141649914","display_name":"Nanchang University","ror":"https://ror.org/042v6xz23","country_code":"CN","type":"education","lineage":["https://openalex.org/I141649914"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhao Wang","raw_affiliation_strings":["Department of Electronic Information Engineering, Nanchang University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Information Engineering, Nanchang University, Nanchang, China","institution_ids":["https://openalex.org/I141649914"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I141649914"],"apc_list":null,"apc_paid":null,"fwci":0.988,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.75598829,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2104","last_page":"2108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9977999925613403,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9976999759674072,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6005731821060181},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.599203884601593},{"id":"https://openalex.org/keywords/deblurring","display_name":"Deblurring","score":0.5957920551300049},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5525675415992737},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5312264561653137},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.49159368872642517},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.48705795407295227},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.4597198963165283},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.45049795508384705},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.4454885423183441},{"id":"https://openalex.org/keywords/structure-tensor","display_name":"Structure tensor","score":0.42766818404197693},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42613011598587036},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42513808608055115},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.39130258560180664},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35198140144348145},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2452700138092041}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6005731821060181},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.599203884601593},{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.5957920551300049},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5525675415992737},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5312264561653137},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.49159368872642517},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.48705795407295227},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.4597198963165283},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.45049795508384705},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.4454885423183441},{"id":"https://openalex.org/C113315163","wikidata":"https://www.wikidata.org/wiki/Q7625159","display_name":"Structure tensor","level":3,"score":0.42766818404197693},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42613011598587036},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42513808608055115},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39130258560180664},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35198140144348145},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2452700138092041},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296653","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296653","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1476376401","https://openalex.org/W1967077133","https://openalex.org/W1995665965","https://openalex.org/W2011775600","https://openalex.org/W2014311222","https://openalex.org/W2018990310","https://openalex.org/W2020741214","https://openalex.org/W2030351687","https://openalex.org/W2030928609","https://openalex.org/W2049588365","https://openalex.org/W2056469265","https://openalex.org/W2061354873","https://openalex.org/W2081962379","https://openalex.org/W2091449379","https://openalex.org/W2095906131","https://openalex.org/W2099628070","https://openalex.org/W2113598499","https://openalex.org/W2117865218","https://openalex.org/W2118963448","https://openalex.org/W2130184048","https://openalex.org/W2135089338","https://openalex.org/W2154011501","https://openalex.org/W2166782149","https://openalex.org/W2168668658","https://openalex.org/W2198155329","https://openalex.org/W2254389401","https://openalex.org/W2427936214","https://openalex.org/W6674415343","https://openalex.org/W6675036773","https://openalex.org/W6691716425"],"related_works":["https://openalex.org/W2031788393","https://openalex.org/W791927757","https://openalex.org/W2182590612","https://openalex.org/W3153582293","https://openalex.org/W2905397092","https://openalex.org/W2269775642","https://openalex.org/W3080537281","https://openalex.org/W2289746762","https://openalex.org/W2139384960","https://openalex.org/W2594717635"],"abstract_inverted_index":{"Image":[0],"prior":[1],"information":[2],"is":[3,36,125,139],"a":[4,18,33,72,128],"determinative":[5],"factor":[6],"to":[7,60,101,112],"tackle":[8],"with":[9,110],"the":[10,56,62,78,88,91,107,122],"ill-posed":[11],"problem.":[12],"In":[13,95],"this":[14,96,103,135],"paper,":[15],"we":[16,98],"present":[17],"multi-filters":[19,68],"guided":[20],"low-rank":[21,34,57,73,129],"tensor":[22,35,58,74,136],"coding":[23,59,75],"(MF-LRTC)":[24],"model":[25],"for":[26,41],"image":[27,109,142,145],"restoration.":[28],"The":[29,51,131],"appeal":[30],"of":[31,55,90,134],"constructing":[32],"obvious":[37],"in":[38,141],"many":[39],"cases":[40],"data":[42],"that":[43],"naturally":[44],"comes":[45],"from":[46,121],"different":[47],"scales":[48],"and":[49,86,147],"directions.":[50],"MF-LRTC":[52],"takes":[53],"advantages":[54],"capture":[61],"sparse":[63,93],"convolutional":[64],"features":[65],"generated":[66],"by":[67,105],"representation.":[69,94],"Using":[70],"such":[71],"would":[76],"reduce":[77],"redundancy":[79],"between":[80],"feature":[81],"vectors":[82],"at":[83],"neighboring":[84],"locations":[85],"improve":[87],"efficiency":[89],"overall":[92],"work,":[97],"are":[99],"committed":[100],"achieving":[102],"goal":[104],"convoluting":[106],"target":[108],"filters":[111],"formulate":[113],"multi-features":[114,123],"images.":[115],"Then":[116],"similarity-grouped":[117],"cube":[118],"set":[119],"extracted":[120],"images":[124],"regarded":[126],"as":[127],"tensor.":[130],"potential":[132],"effectiveness":[133],"construction":[137],"strategy":[138],"demonstrated":[140],"restoration":[143],"including":[144],"deblurring":[146],"compressed":[148],"sensing":[149],"(CS)":[150],"applications.":[151]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":3}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
