{"id":"https://openalex.org/W4372264244","doi":"https://doi.org/10.1109/icassp49357.2023.10096242","title":"Hyperspectral Image Denoising Via Nonlocal Rank Residual Modeling","display_name":"Hyperspectral Image Denoising Via Nonlocal Rank Residual Modeling","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372264244","doi":"https://doi.org/10.1109/icassp49357.2023.10096242"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10096242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10096242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5032774989","display_name":"Zhiyuan Zha","orcid":"https://orcid.org/0000-0002-5515-5339"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Zhiyuan Zha","raw_affiliation_strings":["Nanyang Technological University,School of Electrical &#x0026; Electronic Engineering,Singapore,639798"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,School of Electrical &#x0026; Electronic Engineering,Singapore,639798","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024709593","display_name":"Bihan Wen","orcid":"https://orcid.org/0000-0002-6874-6453"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Bihan Wen","raw_affiliation_strings":["Nanyang Technological University,School of Electrical &#x0026; Electronic Engineering,Singapore,639798"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,School of Electrical &#x0026; Electronic Engineering,Singapore,639798","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004504634","display_name":"Xin Yuan","orcid":"https://orcid.org/0009-0002-7714-1330"},"institutions":[{"id":"https://openalex.org/I3133055985","display_name":"Westlake University","ror":"https://ror.org/05hfa4n20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133055985"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Yuan","raw_affiliation_strings":["Westlake University,School of Engineering,Hangzhou,China,310024"],"affiliations":[{"raw_affiliation_string":"Westlake University,School of Engineering,Hangzhou,China,310024","institution_ids":["https://openalex.org/I3133055985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037979193","display_name":"Jiantao Zhou","orcid":"https://orcid.org/0000-0002-6015-2618"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Jiantao Zhou","raw_affiliation_strings":["University of Macau,Department of Computer and Information Science,Macau,China,999078"],"affiliations":[{"raw_affiliation_string":"University of Macau,Department of Computer and Information Science,Macau,China,999078","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034427070","display_name":"Ce Zhu","orcid":"https://orcid.org/0000-0001-7607-707X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ce Zhu","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Information and Communication Engineering,Chengdu,China,611731"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Information and Communication Engineering,Chengdu,China,611731","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5032774989"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.3777,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57971448,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987000226974487,"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7893092036247253},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7019679546356201},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6911476850509644},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.67783522605896},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.669535756111145},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6085935831069946},{"id":"https://openalex.org/keywords/structure-tensor","display_name":"Structure tensor","score":0.5083755850791931},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4976041615009308},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4694843888282776},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4343326687812805},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4333127737045288},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3926902115345001},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.37248069047927856},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36641591787338257},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3255680799484253},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.0670064389705658},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.06522595882415771}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7893092036247253},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7019679546356201},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6911476850509644},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.67783522605896},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.669535756111145},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6085935831069946},{"id":"https://openalex.org/C113315163","wikidata":"https://www.wikidata.org/wiki/Q7625159","display_name":"Structure tensor","level":3,"score":0.5083755850791931},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4976041615009308},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4694843888282776},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4343326687812805},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4333127737045288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3926902115345001},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.37248069047927856},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36641591787338257},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3255680799484253},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0670064389705658},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.06522595882415771},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10096242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10096242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321655","display_name":"Science and Technology Development Fund","ror":"https://ror.org/044vr6g03"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1963826206","https://openalex.org/W1985242206","https://openalex.org/W1994040806","https://openalex.org/W1997201895","https://openalex.org/W2000215628","https://openalex.org/W2011181254","https://openalex.org/W2014311222","https://openalex.org/W2040895929","https://openalex.org/W2048695508","https://openalex.org/W2056370875","https://openalex.org/W2070424424","https://openalex.org/W2095906131","https://openalex.org/W2097073572","https://openalex.org/W2115706991","https://openalex.org/W2133665775","https://openalex.org/W2163886442","https://openalex.org/W2171520281","https://openalex.org/W2743606449","https://openalex.org/W2747865121","https://openalex.org/W2790888198","https://openalex.org/W2907368145","https://openalex.org/W2979001238","https://openalex.org/W2980079746","https://openalex.org/W2991209609","https://openalex.org/W3004433344","https://openalex.org/W3017506038","https://openalex.org/W3134334503","https://openalex.org/W3134510327","https://openalex.org/W3135630532","https://openalex.org/W3216721694","https://openalex.org/W4220945040","https://openalex.org/W4313524890","https://openalex.org/W6662532501","https://openalex.org/W6784398640"],"related_works":["https://openalex.org/W89301254","https://openalex.org/W2623954137","https://openalex.org/W2535084101","https://openalex.org/W2015754241","https://openalex.org/W1997494252","https://openalex.org/W3174244707","https://openalex.org/W3206725971","https://openalex.org/W2944675036","https://openalex.org/W2052072320","https://openalex.org/W2385280846"],"abstract_inverted_index":{"Nonlocal":[0],"low-rank":[1],"(LR)":[2],"tensor":[3,55,81,113],"modeling":[4],"has":[5],"shown":[6],"great":[7],"potential":[8],"in":[9,49,73,77,181],"hyperspectral":[10],"image":[11],"(HSI)":[12],"denoising,":[13,106],"which":[14,66,107],"first":[15,123],"uses":[16],"the":[17,53,61,110,116,129,136,141,145,151,167,176,182,211,225],"nonlocal":[18,32,45,63,97,131,147,154,203],"self-similarity":[19],"(NSS)":[20],"prior":[21,171],"to":[22,29,69,86,159,174,196],"search":[23],"for":[24,102,229],"many":[25,216],"similar":[26],"full-band":[27,33,46,64,132,148,155,204],"patches":[28],"form":[30],"three-dimensional":[31],"groups":[34],"(tensors),":[35],"and":[36,83,139,202],"then":[37,140],"usually":[38],"enforces":[39],"an":[40],"LR":[41,54,164,170],"penalty":[42],"on":[43],"each":[44],"group.":[47],"However,":[48],"most":[50],"existing":[51],"methods,":[52],"is":[56,67,157,172,232],"only":[57],"approximated":[58],"directly":[59],"from":[60],"degraded":[62],"tensor,":[65],"subject":[68],"certain":[70],"issues":[71],"(e.g.,":[72],"heavy":[74],"noise":[75],"environments)":[76],"obtaining":[78],"a":[79,95,125,161,189],"suboptimal":[80],"approximation,":[82],"thus":[84],"leading":[85],"unsatisfactory":[87],"denoising":[88,184,219,231],"results.":[89],"In":[90],"this":[91,120],"paper,":[92],"we":[93,122,187],"propose":[94],"novel":[96],"rank":[98,117,142],"residual":[99,143],"(NRR)":[100],"approach":[101],"highly":[103],"effective":[104,192],"HSI":[105,180,218,230],"progressively":[108],"approximates":[109],"underlying":[111],"L-R":[112],"via":[114],"minimizing":[115],"residual.":[118],"Towards":[119],"end,":[121],"obtain":[124],"good":[126],"estimate":[127],"of":[128,179,224],"original":[130],"group":[133,149,156],"by":[134],"using":[135],"NSS":[137],"prior,":[138],"between":[144],"de-graded":[146],"with":[150],"corresponding":[152],"estimated":[153],"minimized":[158],"achieve":[160],"more":[162],"accurate":[163],"tensor.":[165],"Moreover,":[166],"global":[168,199],"spectral":[169,177,200],"employed":[173],"reduce":[175],"redundancy":[178],"proposed":[183,212,226],"framework.":[185],"Finally,":[186],"develop":[188],"simple":[190],"yet":[191],"alternating":[193],"minimization":[194],"algorithm":[195,214,228],"jointly":[197],"refine":[198],"information":[201],"groups.":[205],"Experimental":[206],"results":[207],"clearly":[208],"show":[209],"that":[210],"NRR":[213,227],"outperforms":[215],"state-of-the-art":[217],"methods.":[220],"The":[221],"source":[222],"code":[223],"available":[233],"at:":[234],"https://github.com/zhazhiyuan/NRR_HSI_Denoising_Demo.git.":[235]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
