{"id":"https://openalex.org/W4306729205","doi":"https://doi.org/10.1109/tcyb.2022.3208095","title":"Hyperspectral Image Denoising via Weighted Multidirectional Low-Rank Tensor Recovery","display_name":"Hyperspectral Image Denoising via Weighted Multidirectional Low-Rank Tensor Recovery","publication_year":2022,"publication_date":"2022-11-03","ids":{"openalex":"https://openalex.org/W4306729205","doi":"https://doi.org/10.1109/tcyb.2022.3208095","pmid":"https://pubmed.ncbi.nlm.nih.gov/36251897"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2022.3208095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2022.3208095","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","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/A5057904586","display_name":"Yanchi Su","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanchi Su","raw_affiliation_strings":["School of Artificial Intelligence, Jilin University, Changchun, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103066006","display_name":"Haoran Zhu","orcid":"https://orcid.org/0000-0002-7240-2696"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Zhu","raw_affiliation_strings":["School of Artificial Intelligence, Jilin University, Changchun, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030015771","display_name":"Ka\u2010Chun Wong","orcid":"https://orcid.org/0000-0001-6062-733X"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ka-Chun Wong","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029392006","display_name":"Yi Chang","orcid":"https://orcid.org/0000-0003-2697-8093"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Chang","raw_affiliation_strings":["School of Artificial Intelligence, Jilin University, Changchun, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102718214","display_name":"Xiangtao Li","orcid":"https://orcid.org/0000-0002-8716-9823"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangtao Li","raw_affiliation_strings":["School of Artificial Intelligence, Jilin University, Changchun, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5057904586"],"corresponding_institution_ids":["https://openalex.org/I194450716"],"apc_list":null,"apc_paid":null,"fwci":1.9399,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.87594095,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"53","issue":"5","first_page":"2753","last_page":"2766"},"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":0.9997000098228455,"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":0.9987999796867371,"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/subspace-topology","display_name":"Subspace topology","score":0.7929275035858154},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7699160575866699},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.7014922499656677},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5711175799369812},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5613817572593689},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5495737791061401},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5248282551765442},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5155782103538513},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.489362895488739},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46576428413391113},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.44995197653770447},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4257770776748657},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2774333953857422}],"concepts":[{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7929275035858154},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7699160575866699},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7014922499656677},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5711175799369812},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5613817572593689},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5495737791061401},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5248282551765442},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5155782103538513},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.489362895488739},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46576428413391113},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.44995197653770447},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4257770776748657},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2774333953857422},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2022.3208095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2022.3208095","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","raw_type":"journal-article"},{"id":"pmid:36251897","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36251897","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 cybernetics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6600000262260437,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3605434345","display_name":null,"funder_award_id":"62076109","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1944540851","https://openalex.org/W1974933922","https://openalex.org/W1975900269","https://openalex.org/W1994040806","https://openalex.org/W2020461703","https://openalex.org/W2048695508","https://openalex.org/W2070424424","https://openalex.org/W2091449379","https://openalex.org/W2095906131","https://openalex.org/W2103559027","https://openalex.org/W2104050041","https://openalex.org/W2108598243","https://openalex.org/W2136251662","https://openalex.org/W2146842127","https://openalex.org/W2163886442","https://openalex.org/W2167400582","https://openalex.org/W2187214659","https://openalex.org/W2207282238","https://openalex.org/W2221872968","https://openalex.org/W2237974960","https://openalex.org/W2289756263","https://openalex.org/W2336406062","https://openalex.org/W2462946880","https://openalex.org/W2464748116","https://openalex.org/W2506106863","https://openalex.org/W2585357012","https://openalex.org/W2735711969","https://openalex.org/W2737196263","https://openalex.org/W2743606449","https://openalex.org/W2747865121","https://openalex.org/W2748530166","https://openalex.org/W2764207251","https://openalex.org/W2790528326","https://openalex.org/W2805465265","https://openalex.org/W2806155925","https://openalex.org/W2913349789","https://openalex.org/W2914736033","https://openalex.org/W2962737939","https://openalex.org/W2963150697","https://openalex.org/W2964214749","https://openalex.org/W2972301798","https://openalex.org/W2979001238","https://openalex.org/W2980079746","https://openalex.org/W2991209609","https://openalex.org/W3012136461","https://openalex.org/W3012854509","https://openalex.org/W3017506038","https://openalex.org/W3098435832","https://openalex.org/W3100203369","https://openalex.org/W3107769984","https://openalex.org/W3118914778","https://openalex.org/W3127225435","https://openalex.org/W3133237820","https://openalex.org/W3164173661","https://openalex.org/W4240580737","https://openalex.org/W4280563105","https://openalex.org/W4282929851","https://openalex.org/W6620707391","https://openalex.org/W6673357430","https://openalex.org/W6752237900","https://openalex.org/W6838929104"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W2060875994","https://openalex.org/W2027399350","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2890370013","https://openalex.org/W3209466624"],"abstract_inverted_index":{"Recently,":[0],"low-rank":[1,51,87],"tensor":[2,105,116],"recovery":[3,117],"methods":[4,23],"based":[5],"on":[6],"subspace":[7,55],"representation":[8],"have":[9],"received":[10],"increased":[11],"attention":[12],"in":[13,53,71,89,170],"the":[14,26,35,50,54,59,63,72,104,110,114,137,151,164,167],"field":[15],"of":[16,166],"hyperspectral":[17],"image":[18],"(HSI)":[19],"denoising.":[20,172],"Unfortunately,":[21],"those":[22],"usually":[24],"analyze":[25],"prior":[27],"structural":[28],"information":[29],"within":[30],"different":[31,96],"dimensions":[32],"indiscriminately,":[33],"ignoring":[34],"differences":[36],"between":[37],"modes,":[38],"leaving":[39],"substantial":[40],"room":[41],"for":[42,122],"improvement.":[43],"In":[44],"this":[45],"article,":[46],"we":[47,82],"first":[48],"consider":[49],"properties":[52],"and":[56,75,146],"prove":[57],"that":[58,80,150],"structure":[60],"correlation":[61,77],"across":[62],"nonlocal":[64],"self-similarity":[65],"mode":[66,92],"is":[67,93,127],"much":[68],"stronger":[69],"than":[70],"spatial":[73],"sparsity":[74],"spectral":[76],"modes.":[78],"On":[79],"basis,":[81],"introduce":[83],"a":[84,95],"new":[85],"multidirectional":[86],"regularization,":[88],"which":[90,161],"each":[91],"assigned":[94],"weight":[97],"to":[98,102],"characterize":[99],"its":[100],"contribution":[101],"estimating":[103],"rank.":[106],"After":[107],"that,":[108],"integrating":[109],"proposed":[111,130,152,168],"regularization":[112],"with":[113,144],"subspace-based":[115],"framework,":[118],"an":[119],"optimization":[120],"model":[121,131],"HSI":[123,158,171],"mixed":[124],"noise":[125],"removal":[126],"developed.":[128],"The":[129],"can":[132],"be":[133],"addressed":[134],"efficiently":[135],"via":[136],"alternating":[138],"minimization":[139],"algorithm.":[140],"Extensive":[141],"experiments":[142],"implemented":[143],"synthetic":[145],"real":[147],"data":[148],"demonstrate":[149],"method":[153],"significantly":[154],"outperforms":[155],"other":[156],"state-of-the-art":[157],"denoising":[159],"methods,":[160],"clearly":[162],"indicates":[163],"effectiveness":[165],"approach":[169]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}