{"id":"https://openalex.org/W4312909115","doi":"https://doi.org/10.1109/tgrs.2022.3217097","title":"Nonlocal Spatial\u2013Spectral Neural Network for Hyperspectral Image Denoising","display_name":"Nonlocal Spatial\u2013Spectral Neural Network for Hyperspectral Image Denoising","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312909115","doi":"https://doi.org/10.1109/tgrs.2022.3217097"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3217097","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3217097","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10072/420776","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062218391","display_name":"Guanyiman Fu","orcid":"https://orcid.org/0000-0002-2256-5876"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanyiman Fu","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-2256-5876","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033291716","display_name":"Fengchao Xiong","orcid":"https://orcid.org/0000-0002-9753-4919"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengchao Xiong","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-9753-4919","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037595310","display_name":"Jianfeng Lu","orcid":"https://orcid.org/0000-0002-9190-507X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Lu","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-9190-507X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100781212","display_name":"Jun Zhou","orcid":"https://orcid.org/0000-0001-5822-8233"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jun Zhou","raw_affiliation_strings":["School of Information and Communication Technology, Griffith University, Nathan, QLD, Australia"],"raw_orcid":"https://orcid.org/0000-0001-5822-8233","affiliations":[{"raw_affiliation_string":"School of Information and Communication Technology, Griffith University, Nathan, QLD, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059857918","display_name":"Yuntao Qian","orcid":"https://orcid.org/0000-0002-7418-5891"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuntao Qian","raw_affiliation_strings":["College of Computer Science, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7418-5891","affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3491,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.90154121,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994000196456909,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.835882306098938},{"id":"https://openalex.org/keywords/spatial-correlation","display_name":"Spatial correlation","score":0.6573135256767273},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6053780913352966},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.586585521697998},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5774420499801636},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5752748847007751},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5582178831100464},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.49005353450775146},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.48088982701301575},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4800247251987457},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4794529974460602},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4598664939403534},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.43836134672164917},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43659764528274536},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31953930854797363},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2914905250072479},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14204153418540955}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.835882306098938},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.6573135256767273},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6053780913352966},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.586585521697998},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5774420499801636},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5752748847007751},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5582178831100464},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.49005353450775146},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.48088982701301575},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4800247251987457},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4794529974460602},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4598664939403534},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.43836134672164917},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43659764528274536},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31953930854797363},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2914905250072479},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14204153418540955},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2022.3217097","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3217097","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/420776","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/420776","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal article"}],"best_oa_location":{"id":"pmh:oai:research-repository.griffith.edu.au:10072/420776","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/420776","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.47999998927116394}],"awards":[{"id":"https://openalex.org/G5507728153","display_name":"\u9065\u611f\u5f71\u50cf\u6b27\u6c0f\u548c\u975e\u6b27\u7ed3\u6784\u534f\u540c\u5efa\u6a21\u548c\u8868\u793a\u5b66\u4e60\u7814\u7a76","funder_award_id":"62071421","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8405162171","display_name":null,"funder_award_id":"62002169","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8688142813","display_name":null,"funder_award_id":"BK20200466","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W1928626817","https://openalex.org/W1974438823","https://openalex.org/W1985242206","https://openalex.org/W1994040806","https://openalex.org/W2039596145","https://openalex.org/W2056370875","https://openalex.org/W2064675550","https://openalex.org/W2069231830","https://openalex.org/W2070424424","https://openalex.org/W2072026894","https://openalex.org/W2095906131","https://openalex.org/W2163886442","https://openalex.org/W2621042378","https://openalex.org/W2743255627","https://openalex.org/W2747865121","https://openalex.org/W2770790879","https://openalex.org/W2790888198","https://openalex.org/W2793237446","https://openalex.org/W2794209590","https://openalex.org/W2794215437","https://openalex.org/W2806155925","https://openalex.org/W2919868964","https://openalex.org/W2935130647","https://openalex.org/W2950297649","https://openalex.org/W2952436057","https://openalex.org/W2963091558","https://openalex.org/W2963174729","https://openalex.org/W2964179170","https://openalex.org/W2972029982","https://openalex.org/W2979001238","https://openalex.org/W2981689412","https://openalex.org/W2982007765","https://openalex.org/W2984522085","https://openalex.org/W2991209609","https://openalex.org/W2999482976","https://openalex.org/W3007139997","https://openalex.org/W3009971095","https://openalex.org/W3013064625","https://openalex.org/W3013853001","https://openalex.org/W3016056257","https://openalex.org/W3021083191","https://openalex.org/W3045351696","https://openalex.org/W3098435832","https://openalex.org/W3104896896","https://openalex.org/W3107702424","https://openalex.org/W3109018774","https://openalex.org/W3118496544","https://openalex.org/W3118914778","https://openalex.org/W3131515870","https://openalex.org/W3147216634","https://openalex.org/W3154593456","https://openalex.org/W3159843306","https://openalex.org/W3197539572","https://openalex.org/W3205847273","https://openalex.org/W3216721694","https://openalex.org/W4200607031","https://openalex.org/W4206806028","https://openalex.org/W4220945040","https://openalex.org/W4226024412","https://openalex.org/W4242059867","https://openalex.org/W6691800262","https://openalex.org/W6738486038","https://openalex.org/W6764398373","https://openalex.org/W6784398640"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W2070598848","https://openalex.org/W2019190440","https://openalex.org/W3034864990"],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1],"(HSI)":[2],"denoising":[3,19,51,166,173],"is":[4,65,129],"an":[5],"essential":[6],"preprocessing":[7],"step":[8],"to":[9,121,145,185],"improve":[10],"the":[11,24,54,68,74,102,113,123,137,149,152,157,171],"quality":[12],"of":[13,17,27,148,175],"HSIs.":[14],"The":[15,85,105,188],"difficulty":[16],"HSI":[18,50],"lies":[20],"in":[21,58],"effectively":[22,141],"modeling":[23,147],"intrinsic":[25],"characteristics":[26],"HSIs,":[28],"such":[29],"as":[30],"spatial-spectral":[31,45,76,103,150],"correlation,":[32,35,151,155,160],"global":[33,124,153],"spectral":[34,125,154],"and":[36,71,80,94,108,117,134,142,156,180],"nonlocal":[37,44,81,158],"spatial":[38,139,159],"correlation.":[39,104,126],"This":[40],"paper":[41],"introduces":[42],"a":[43,59,164],"neural":[46],"network":[47,110],"(NSSNN)":[48],"for":[49],"by":[52],"considering":[53],"above":[55],"three":[56],"factors":[57],"unified":[60],"network.":[61,97],"More":[62],"specifically,":[63],"NSSNN":[64,162],"based":[66,130],"on":[67,131,178],"residual":[69],"U-Net":[70],"embedded":[72],"with":[73],"introduced":[75],"recurrent":[77,114],"(SSR)":[78],"blocks":[79],"self-similarity":[82],"(NSS)":[83],"blocks.":[84],"SSR":[86],"block":[87,128],"comprises":[88],"3D":[89,98],"convolutions,":[90],"one":[91,95],"light":[92,106],"recurrence,":[93],"highway":[96,109],"convolution":[99],"helps":[100],"exploit":[101,136],"recurrence":[107],"make":[111],"up":[112],"computation":[115],"component":[116],"refined":[118],"component,":[119],"respectively,":[120],"model":[122],"NSS":[127],"crisscross":[132],"attention":[133],"can":[135],"long-range":[138],"contexts":[140],"efficiently.":[143],"Attributing":[144],"effective":[146],"our":[161,176],"has":[163],"strong":[165],"ability.":[167],"Extensive":[168],"experiments":[169],"show":[170],"superior":[172],"effectiveness":[174],"method":[177],"synthetic":[179],"real-world":[181],"datasets":[182],"when":[183],"compared":[184],"alternative":[186],"methods.":[187],"source":[189],"code":[190],"will":[191],"be":[192],"available":[193],"at":[194],"https://github.com/lronkitty/NSSNN.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":7}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}