{"id":"https://openalex.org/W4386281244","doi":"https://doi.org/10.1109/jstars.2023.3310215","title":"Multibranch Separable 3-D Convolutional Neural Network for Hyperspectral Image Denoising","display_name":"Multibranch Separable 3-D Convolutional Neural Network for Hyperspectral Image Denoising","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386281244","doi":"https://doi.org/10.1109/jstars.2023.3310215"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2023.3310215","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2023.3310215","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2023.3310215","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090531606","display_name":"Haitao Yin","orcid":"https://orcid.org/0000-0003-2975-2188"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haitao Yin","raw_affiliation_strings":["College of Automation and College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-2975-2188","affiliations":[{"raw_affiliation_string":"College of Automation and College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100353679","display_name":"Hao Chen","orcid":"https://orcid.org/0009-0007-0600-4351"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Chen","raw_affiliation_strings":["College of Automation and College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0007-0600-4351","affiliations":[{"raw_affiliation_string":"College of Automation and College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":{"value":1800,"currency":"USD","value_usd":1800},"apc_paid":{"value":1800,"currency":"USD","value_usd":1800},"fwci":0.3799,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.55375889,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"16","issue":null,"first_page":"8034","last_page":"8048"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.8162523508071899},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7594135999679565},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7160670161247253},{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.6977024674415588},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6557985544204712},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6180769205093384},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5619516372680664},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5545853972434998},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5046497583389282},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4404413104057312},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4351470470428467},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.429423987865448},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4102601110935211},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27686673402786255},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.26098042726516724}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.8162523508071899},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7594135999679565},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7160670161247253},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.6977024674415588},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6557985544204712},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6180769205093384},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5619516372680664},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5545853972434998},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5046497583389282},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4404413104057312},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4351470470428467},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.429423987865448},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4102601110935211},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27686673402786255},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26098042726516724},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2023.3310215","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2023.3310215","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:87b002f86e3044608a688721eaa8c6b5","is_oa":true,"landing_page_url":"https://doaj.org/article/87b002f86e3044608a688721eaa8c6b5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 8034-8048 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2023.3310215","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2023.3310215","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4399999976158142}],"awards":[{"id":"https://openalex.org/G10643888","display_name":"\u57fa\u4e8e\u5f20\u91cf\u7a00\u758f\u6df1\u5ea6\u5b66\u4e60\u7684\u9ad8\u7ef4\u9065\u611f\u56fe\u50cf\u878d\u5408\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61971237","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G393642581","display_name":null,"funder_award_id":"202215","funder_id":"https://openalex.org/F4320316084","funder_display_name":"China Computer Federation"}],"funders":[{"id":"https://openalex.org/F4320316084","display_name":"China Computer Federation","ror":"https://ror.org/015xj5w40"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W825199928","https://openalex.org/W1928626817","https://openalex.org/W1944540851","https://openalex.org/W1974438823","https://openalex.org/W1994040806","https://openalex.org/W2039596145","https://openalex.org/W2053514113","https://openalex.org/W2053950384","https://openalex.org/W2082590963","https://openalex.org/W2087263574","https://openalex.org/W2129891925","https://openalex.org/W2133665775","https://openalex.org/W2140702875","https://openalex.org/W2155124307","https://openalex.org/W2161073299","https://openalex.org/W2183341477","https://openalex.org/W2221872968","https://openalex.org/W2289756263","https://openalex.org/W2414009677","https://openalex.org/W2464748116","https://openalex.org/W2508457857","https://openalex.org/W2585357012","https://openalex.org/W2614611154","https://openalex.org/W2735711969","https://openalex.org/W2747865121","https://openalex.org/W2790888198","https://openalex.org/W2793237446","https://openalex.org/W2794215437","https://openalex.org/W2806155925","https://openalex.org/W2905232803","https://openalex.org/W2914736033","https://openalex.org/W2919868964","https://openalex.org/W2935130647","https://openalex.org/W2948097295","https://openalex.org/W2963820951","https://openalex.org/W2964179170","https://openalex.org/W2964214749","https://openalex.org/W2975506318","https://openalex.org/W2980079746","https://openalex.org/W2984522085","https://openalex.org/W2997123853","https://openalex.org/W3013064625","https://openalex.org/W3015299897","https://openalex.org/W3015466860","https://openalex.org/W3032341357","https://openalex.org/W3035254087","https://openalex.org/W3095207884","https://openalex.org/W3098435832","https://openalex.org/W3103982318","https://openalex.org/W3154593456","https://openalex.org/W3168931281","https://openalex.org/W3201553497","https://openalex.org/W3211474784","https://openalex.org/W3215551818","https://openalex.org/W4226430688","https://openalex.org/W4285119471","https://openalex.org/W4297775537","https://openalex.org/W4312324774","https://openalex.org/W4312909115","https://openalex.org/W4313012878","https://openalex.org/W4319990441","https://openalex.org/W6623232459","https://openalex.org/W6737664043"],"related_works":["https://openalex.org/W2317401237","https://openalex.org/W1990800631","https://openalex.org/W3158431807","https://openalex.org/W2530952058","https://openalex.org/W2582836483","https://openalex.org/W2167120702","https://openalex.org/W2579567122","https://openalex.org/W4299366318","https://openalex.org/W4297580547","https://openalex.org/W2912065050"],"abstract_inverted_index":{"3D":[0,25,64,81,88,101,108,147,165,174,189],"convolutional":[1],"neural":[2],"network":[3],"(CNN)":[4],"offers":[5],"a":[6,38,60,93,111,116,145,183],"great":[7],"potential":[8],"spatial-spectral":[9,33,70,96,138],"representation":[10],"for":[11,135,149],"hyperspectral":[12],"image":[13],"(HSI),":[14],"and":[15,36,54,58,78,115,130,181,204],"has":[16],"achieved":[17],"promising":[18],"HSI":[19,134,150,207],"denoising":[20],"performance.":[21],"However,":[22],"the":[23,50,85,106,158],"current":[24],"CNNs":[26],"still":[27],"suffer":[28],"from":[29,49],"limited":[30],"non-uniform":[31,95],"multi-component":[32],"features":[34,97,132],"encoding,":[35],"incur":[37],"high":[39],"computation":[40],"burden.":[41],"To":[42],"address":[43],"these":[44],"issues,":[45],"we":[46,143],"draw":[47],"inspiration":[48],"success":[51],"of":[52,163],"multi-branch":[53],"separable":[55,80,87,100,173],"convolution":[56,102,109,114,166,175],"perspectives,":[57],"propose":[59],"plug-and-play":[61],"Multi-branch":[62],"Separable":[63],"Convolution":[65],"Block":[66],"(MS3CB)":[67],"with":[68],"different":[69],"receptive":[71],"fields.":[72],"Specifically,":[73],"MS3CB":[74,104,156],"comprises":[75],"mixed":[76],"regular":[77],"non-regular":[79,86],"branches,":[82],"in":[83,103,133],"which":[84,120,154],"branch":[89],"attempts":[90],"to":[91],"provide":[92],"meaningful":[94],"extractor.":[98],"The":[99],"factorizes":[105],"standard":[107,164,188],"into":[110],"2D":[112],"spatial":[113,129],"1D":[117],"spectral":[118,131],"convolution,":[119],"not":[121],"only":[122],"reduces":[123,177],"model":[124],"size,":[125],"but":[126],"also":[127],"decouples":[128],"more":[136],"flexible":[137],"representation.":[139],"Based":[140],"on":[141,201],"MS3CB,":[142],"develop":[144],"novel":[146],"U-Net":[148],"Denoising,":[151],"called":[152],"HSDU-Net,":[153],"uses":[155],"as":[157],"basic":[159],"building":[160],"block":[161,176],"instead":[162],"block.":[167],"We":[168],"empirically":[169],"verify":[170],"that":[171,195],"our":[172],"about":[178],"64.6%":[179],"parameters":[180],"achieves":[182],"certain":[184],"performance":[185],"gain":[186],"over":[187],"convolution.":[190],"Extensive":[191],"experiments":[192],"further":[193],"demonstrate":[194],"HSDU-Net":[196],"surpasses":[197],"several":[198],"latest":[199],"baselines":[200],"various":[202],"synthetic":[203],"real":[205],"noisy":[206],"datasets.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}