{"id":"https://openalex.org/W2595400155","doi":"https://doi.org/10.1117/12.2268435","title":"Video denoising using low rank tensor decomposition","display_name":"Video denoising using low rank tensor decomposition","publication_year":2017,"publication_date":"2017-03-17","ids":{"openalex":"https://openalex.org/W2595400155","doi":"https://doi.org/10.1117/12.2268435","mag":"2595400155"},"language":"en","primary_location":{"id":"doi:10.1117/12.2268435","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2268435","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/A5071624109","display_name":"Lihua Gui","orcid":null},"institutions":[{"id":"https://openalex.org/I185365093","display_name":"Saitama Institute of Technology","ror":"https://ror.org/01pkeax38","country_code":"JP","type":"education","lineage":["https://openalex.org/I185365093"]},{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Lihua Gui","raw_affiliation_strings":["Saitama Institute of Technology (Japan)","RIKEN Brain Science Institute (Japan)"],"affiliations":[{"raw_affiliation_string":"Saitama Institute of Technology (Japan)","institution_ids":["https://openalex.org/I185365093"]},{"raw_affiliation_string":"RIKEN Brain Science Institute (Japan)","institution_ids":["https://openalex.org/I2800939219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014572194","display_name":"Gaochao Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]},{"id":"https://openalex.org/I185365093","display_name":"Saitama Institute of Technology","ror":"https://ror.org/01pkeax38","country_code":"JP","type":"education","lineage":["https://openalex.org/I185365093"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Gaochao Cui","raw_affiliation_strings":["Saitama Institute of Technology (Japan)","RIKEN Brain Science Institute (Japan)"],"affiliations":[{"raw_affiliation_string":"Saitama Institute of Technology (Japan)","institution_ids":["https://openalex.org/I185365093"]},{"raw_affiliation_string":"RIKEN Brain Science Institute (Japan)","institution_ids":["https://openalex.org/I2800939219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083182987","display_name":"Qibin Zhao","orcid":"https://orcid.org/0000-0002-4442-3182"},"institutions":[{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]},{"id":"https://openalex.org/I185365093","display_name":"Saitama Institute of Technology","ror":"https://ror.org/01pkeax38","country_code":"JP","type":"education","lineage":["https://openalex.org/I185365093"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Qibin Zhao","raw_affiliation_strings":["Saitama Institute of Technology (Japan)","RIKEN Brain Science Institute (Japan)"],"affiliations":[{"raw_affiliation_string":"Saitama Institute of Technology (Japan)","institution_ids":["https://openalex.org/I185365093"]},{"raw_affiliation_string":"RIKEN Brain Science Institute (Japan)","institution_ids":["https://openalex.org/I2800939219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100450579","display_name":"Dongsheng Wang","orcid":"https://orcid.org/0000-0001-7341-2776"},"institutions":[{"id":"https://openalex.org/I185365093","display_name":"Saitama Institute of Technology","ror":"https://ror.org/01pkeax38","country_code":"JP","type":"education","lineage":["https://openalex.org/I185365093"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Dongsheng Wang","raw_affiliation_strings":["Saitama Institute of Technology (Japan)"],"affiliations":[{"raw_affiliation_string":"Saitama Institute of Technology (Japan)","institution_ids":["https://openalex.org/I185365093"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018676117","display_name":"Andrzej Cichocki","orcid":"https://orcid.org/0000-0002-8364-7226"},"institutions":[{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Andrzej Cichocki","raw_affiliation_strings":["RIKEN Brain Science Institute (Japan)"],"affiliations":[{"raw_affiliation_string":"RIKEN Brain Science Institute (Japan)","institution_ids":["https://openalex.org/I2800939219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101714954","display_name":"Jianting Cao","orcid":"https://orcid.org/0000-0002-7749-7188"},"institutions":[{"id":"https://openalex.org/I185365093","display_name":"Saitama Institute of Technology","ror":"https://ror.org/01pkeax38","country_code":"JP","type":"education","lineage":["https://openalex.org/I185365093"]},{"id":"https://openalex.org/I4210110652","display_name":"RIKEN","ror":"https://ror.org/01sjwvz98","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jianting Cao","raw_affiliation_strings":["Saitama Institute of Technology (Japan)","RIKEN Brian Science Institute (Japan)"],"affiliations":[{"raw_affiliation_string":"Saitama Institute of Technology (Japan)","institution_ids":["https://openalex.org/I185365093"]},{"raw_affiliation_string":"RIKEN Brian Science Institute (Japan)","institution_ids":["https://openalex.org/I4210110652"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5071624109"],"corresponding_institution_ids":["https://openalex.org/I185365093","https://openalex.org/I2800939219"],"apc_list":null,"apc_paid":null,"fwci":0.3641,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.67294928,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"10341","issue":null,"first_page":"103410V","last_page":"103410V"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9987999796867371,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9980000257492065,"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/computer-science","display_name":"Computer science","score":0.657273530960083},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6149131059646606},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.5814154148101807},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5481921434402466},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.46091774106025696},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.417153924703598},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.4118487536907196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3972775936126709},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35378438234329224},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10502320528030396},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08609166741371155},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.07417407631874084}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.657273530960083},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6149131059646606},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.5814154148101807},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5481921434402466},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.46091774106025696},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.417153924703598},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.4118487536907196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3972775936126709},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35378438234329224},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10502320528030396},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08609166741371155},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.07417407631874084},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2268435","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2268435","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W792141054","https://openalex.org/W2017399967","https://openalex.org/W2056370875","https://openalex.org/W2107214962","https://openalex.org/W2137577808","https://openalex.org/W2147512299","https://openalex.org/W2326762225","https://openalex.org/W2527353150","https://openalex.org/W2536599074","https://openalex.org/W6680683657","https://openalex.org/W6728784816"],"related_works":["https://openalex.org/W2781510240","https://openalex.org/W2950186459","https://openalex.org/W2170114491","https://openalex.org/W2897298721","https://openalex.org/W2242624680","https://openalex.org/W2136127937","https://openalex.org/W4290987221","https://openalex.org/W2216309014","https://openalex.org/W3199841771","https://openalex.org/W3006184558"],"abstract_inverted_index":{"Reducing":[0],"noise":[1,31,85,89,111],"in":[2,10,41],"a":[3,48],"video":[4,37,97,116],"sequence":[5,38],"is":[6,17,29,39,102],"of":[7,26,58,121],"vital":[8],"important":[9],"many":[11],"real-world":[12],"applications.":[13],"One":[14],"popular":[15],"method":[16,28,101],"block":[18],"matching":[19],"collaborative":[20,75],"filtering.":[21,76],"However,":[22],"the":[23,35,63,70,80,84,88,110,119],"main":[24],"drawback":[25],"this":[27,44],"that":[30,53],"standard":[32],"deviation":[33],"for":[34,74],"whole":[36],"known":[40],"advance.":[42],"In":[43],"paper,":[45],"we":[46,68,78],"present":[47],"tensor":[49,72],"based":[50],"denoising":[51,117],"framework":[52],"considers":[54],"3D":[55,65],"patches":[56,66],"instead":[57],"2D":[59],"patches.":[60],"By":[61],"collecting":[62],"similar":[64],"non-locally,":[67],"employ":[69],"low-rank":[71],"decomposition":[73],"Since":[77],"specify":[79],"non-informative":[81],"prior":[82],"over":[83],"precision":[86],"parameter,":[87],"variance":[90],"can":[91],"be":[92],"inferred":[93],"automatically":[94],"from":[95],"observed":[96],"data.":[98],"Therefore,":[99],"our":[100,122],"more":[103],"practical,":[104],"which":[105],"does":[106],"not":[107],"require":[108],"knowing":[109],"variance.":[112],"The":[113],"experimental":[114],"on":[115],"demonstrates":[118],"effectiveness":[120],"proposed":[123],"method.":[124]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}