{"id":"https://openalex.org/W2791540268","doi":"https://doi.org/10.1109/vcip.2017.8305141","title":"Low rank regularization exploiting intra and inter patch correlation for image denoising","display_name":"Low rank regularization exploiting intra and inter patch correlation for image denoising","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2791540268","doi":"https://doi.org/10.1109/vcip.2017.8305141","mag":"2791540268"},"language":"en","primary_location":{"id":"doi:10.1109/vcip.2017.8305141","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2017.8305141","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Visual Communications and Image Processing (VCIP)","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/A5079154623","display_name":"Hangfan Liu","orcid":"https://orcid.org/0000-0002-1207-7713"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hangfan Liu","raw_affiliation_strings":["Institute of Digital Media, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Digital Media, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013727612","display_name":"Ruiqin Xiong","orcid":"https://orcid.org/0000-0001-9796-0478"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiqin Xiong","raw_affiliation_strings":["Institute of Digital Media, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Digital Media, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100407381","display_name":"Dong Liu","orcid":"https://orcid.org/0000-0001-9100-2906"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Liu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029102289","display_name":"Feng Wu","orcid":"https://orcid.org/0000-0003-3989-0509"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Wu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018478553","display_name":"Wen Gao","orcid":"https://orcid.org/0000-0002-8070-802X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Gao","raw_affiliation_strings":["Institute of Digital Media, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Digital Media, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2771,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.66808381,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","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/T10688","display_name":"Image and Signal Denoising Methods","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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9995999932289124,"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":0.9983999729156494,"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/regularization","display_name":"Regularization (linguistics)","score":0.6408373713493347},{"id":"https://openalex.org/keywords/latent-image","display_name":"Latent image","score":0.6363065242767334},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5572234988212585},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5055160522460938},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.4983255863189697},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.47900694608688354},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4463474154472351},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4439893066883087},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.44089967012405396},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44057220220565796},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41400736570358276},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32328224182128906},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.25689101219177246}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6408373713493347},{"id":"https://openalex.org/C205372313","wikidata":"https://www.wikidata.org/wiki/Q355645","display_name":"Latent image","level":3,"score":0.6363065242767334},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5572234988212585},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5055160522460938},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.4983255863189697},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47900694608688354},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4463474154472351},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4439893066883087},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.44089967012405396},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44057220220565796},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41400736570358276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32328224182128906},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.25689101219177246},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/vcip.2017.8305141","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2017.8305141","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Visual Communications and Image Processing (VCIP)","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":0.5899999737739563}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1607704809","https://openalex.org/W1915372217","https://openalex.org/W2048695508","https://openalex.org/W2056370875","https://openalex.org/W2100705753","https://openalex.org/W2127870457","https://openalex.org/W2130221818","https://openalex.org/W2136912397","https://openalex.org/W2156242833","https://openalex.org/W2171170856","https://openalex.org/W2203654268","https://openalex.org/W2207282238","https://openalex.org/W2338117771","https://openalex.org/W2512402757","https://openalex.org/W2527004316","https://openalex.org/W6680391196"],"related_works":["https://openalex.org/W4388229682","https://openalex.org/W2353625790","https://openalex.org/W2480327201","https://openalex.org/W2479205379","https://openalex.org/W2006843870","https://openalex.org/W1602455006","https://openalex.org/W3209466624","https://openalex.org/W2905397092","https://openalex.org/W3080537281","https://openalex.org/W2053844550"],"abstract_inverted_index":{"Based":[0],"on":[1],"the":[2,32,35,44,47,75,103,111,114,119,122,140,151,174],"observation":[3],"that":[4,31,46,173],"a":[5],"matrix":[6],"X":[7],"consisted":[8],"of":[9,14,34,102,113,121,157,183],"non-local":[10],"highly-correlated":[11],"patches":[12],"is":[13,55,62,159],"low":[15],"rank,":[16],"many":[17],"image":[18,28,37,87],"restoration":[19],"methods":[20,180],"use":[21,144],"low-rank":[22],"regularization":[23],"to":[24,51,57,63,83,94,108,131,149],"exploit":[25,96],"correlation":[26,85,101],"between":[27],"contents,":[29],"so":[30,106],"uncertainty":[33,112],"unknown":[36],"signal":[38],"can":[39],"be":[40],"reduced.":[41],"To":[42,138],"tackle":[43],"problem":[45,152],"underlying":[48],"cost":[49],"function":[50],"pursue":[52],"minimal":[53],"rank":[54,76],"hard":[56],"solve,":[58],"an":[59,162],"effective":[60],"way":[61],"employ":[64],"smooth":[65],"non-convex":[66],"surrogate":[67],"log":[68],"|XX":[69],"<sup":[70],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[71],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">T</sup>":[72],"|":[73],"for":[74],"penalty.":[77],"Essentially,":[78],"such":[79],"technique":[80,148],"only":[81],"considers":[82],"utilize":[84],"within":[86],"patches.":[88],"In":[89],"this":[90],"paper,":[91],"we":[92,143],"propose":[93],"jointly":[95],"both":[97,133],"intra-":[98,134],"and":[99,116,135,185],"inter-patch":[100,136],"input":[104],"image,":[105],"as":[107],"further":[109],"reduce":[110],"signal,":[115],"thus":[117],"improve":[118],"prediction":[120],"latent":[123],"image.":[124],"The":[125],"corresponding":[126],"two":[127,154],"surrogates":[128],"are":[129],"integrated":[130],"incorporate":[132],"correlation.":[137],"solve":[139],"optimization":[141],"problem,":[142],"iterative":[145],"alternating":[146],"direction":[147],"divide":[150],"into":[153],"subproblems,":[155],"each":[156],"which":[158],"solved":[160],"via":[161],"empirical":[163],"Bayesian":[164],"procedure":[165],"built":[166],"upon":[167],"variational":[168],"approximation.":[169],"Experimental":[170],"results":[171],"show":[172],"proposed":[175],"approach":[176],"outperforms":[177],"several":[178],"state-of-the-art":[179],"in":[181],"terms":[182],"PSNR":[184],"perceptual":[186],"quality.":[187]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}