{"id":"https://openalex.org/W2486845456","doi":"https://doi.org/10.1109/jstars.2016.2574876","title":"GPU-Based Parallel Design of the Hyperspectral Signal Subspace Identification by Minimum Error (HySime)","display_name":"GPU-Based Parallel Design of the Hyperspectral Signal Subspace Identification by Minimum Error (HySime)","publication_year":2016,"publication_date":"2016-07-26","ids":{"openalex":"https://openalex.org/W2486845456","doi":"https://doi.org/10.1109/jstars.2016.2574876","mag":"2486845456"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2016.2574876","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2016.2574876","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":false,"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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100761146","display_name":"Xin Wu","orcid":"https://orcid.org/0000-0002-0389-050X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Wu","raw_affiliation_strings":["School of Physics and Optoelectronic Engineering, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physics and Optoelectronic Engineering, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060262250","display_name":"Bormin Huang","orcid":"https://orcid.org/0000-0001-8275-9536"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]},{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Bormin Huang","raw_affiliation_strings":["Space Science and Engineering Center, University of Wisconsin, Madison, WI, USA","Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Space Science and Engineering Center, University of Wisconsin, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]},{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009116003","display_name":"Lizhe Wang","orcid":"https://orcid.org/0000-0003-2766-0845"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lizhe Wang","raw_affiliation_strings":["Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104023316","display_name":"Jianqi Zhang","orcid":"https://orcid.org/0000-0002-3549-1482"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianqi Zhang","raw_affiliation_strings":["School of Physics and Optoelectronic Engineering, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physics and Optoelectronic Engineering, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":null,"fwci":2.9426,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.9196052,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"9","issue":"9","first_page":"4400","last_page":"4406"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9904999732971191,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9868999719619751,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8735349178314209},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8064429759979248},{"id":"https://openalex.org/keywords/cuda","display_name":"CUDA","score":0.5994539856910706},{"id":"https://openalex.org/keywords/graphics-processing-unit","display_name":"Graphics processing unit","score":0.5860451459884644},{"id":"https://openalex.org/keywords/signal-subspace","display_name":"Signal subspace","score":0.5718772411346436},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5594146251678467},{"id":"https://openalex.org/keywords/massively-parallel","display_name":"Massively parallel","score":0.5329951047897339},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.46456754207611084},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.41953834891319275},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4013798236846924},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39256399869918823},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3817911446094513},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.29299575090408325},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.17438405752182007},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.14011076092720032}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8735349178314209},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8064429759979248},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.5994539856910706},{"id":"https://openalex.org/C2779851693","wikidata":"https://www.wikidata.org/wiki/Q183484","display_name":"Graphics processing unit","level":2,"score":0.5860451459884644},{"id":"https://openalex.org/C2777121530","wikidata":"https://www.wikidata.org/wiki/Q7512739","display_name":"Signal subspace","level":4,"score":0.5718772411346436},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5594146251678467},{"id":"https://openalex.org/C190475519","wikidata":"https://www.wikidata.org/wiki/Q544384","display_name":"Massively parallel","level":2,"score":0.5329951047897339},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.46456754207611084},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.41953834891319275},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4013798236846924},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39256399869918823},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3817911446094513},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.29299575090408325},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.17438405752182007},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.14011076092720032},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstars.2016.2574876","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2016.2574876","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":false,"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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1932474477","display_name":null,"funder_award_id":"61301290","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W164384110","https://openalex.org/W1762731526","https://openalex.org/W1982618228","https://openalex.org/W1987022492","https://openalex.org/W2004001880","https://openalex.org/W2011120242","https://openalex.org/W2014309790","https://openalex.org/W2017414221","https://openalex.org/W2022470997","https://openalex.org/W2048419331","https://openalex.org/W2054389376","https://openalex.org/W2056051416","https://openalex.org/W2058144644","https://openalex.org/W2070424424","https://openalex.org/W2084830040","https://openalex.org/W2095687521","https://openalex.org/W2097900616","https://openalex.org/W2107120407","https://openalex.org/W2116720609","https://openalex.org/W2131274487","https://openalex.org/W2133782497","https://openalex.org/W2148432924","https://openalex.org/W2150379994","https://openalex.org/W2154970996","https://openalex.org/W2159994690","https://openalex.org/W2167583754","https://openalex.org/W2243134569","https://openalex.org/W2306710075","https://openalex.org/W2312997001","https://openalex.org/W2398736067","https://openalex.org/W3143245542","https://openalex.org/W6677463967","https://openalex.org/W6690663885","https://openalex.org/W6698072594"],"related_works":["https://openalex.org/W2148432924","https://openalex.org/W2119534391","https://openalex.org/W2023770367","https://openalex.org/W2503137108","https://openalex.org/W1966576946","https://openalex.org/W2020279179","https://openalex.org/W2765743988","https://openalex.org/W2062253548","https://openalex.org/W2393490604","https://openalex.org/W2393707426"],"abstract_inverted_index":{"Signal":[0],"subspace":[1,29,53],"identification":[2],"provides":[3],"a":[4,22,42,81],"performance":[5,129],"improvement":[6],"in":[7,54,124],"hyperspectral":[8,27,67,134,172],"applications,":[9],"such":[10],"as":[11],"target":[12],"detection,":[13],"spectral":[14],"unmixing,":[15],"and":[16,36,63,112,128,144],"classification.":[17],"The":[18,119,136],"HySime":[19,70,87,165],"method":[20,88,166],"is":[21,46],"well-known":[23],"unsupervised":[24],"approach":[25],"for":[26,89,170],"signal":[28,37,52],"identification.":[30],"It":[31],"computes":[32],"the":[33,51,55,61,66,69,86,102,106,113,131,139,154,164],"estimated":[34],"noise":[35],"correlation":[38],"matrices":[39],"from":[40],"which":[41],"subset":[43],"of":[44,65,85,105,115,126,163],"eigenvectors":[45],"selected":[47],"to":[48,153],"best":[49],"represent":[50],"least":[56],"square":[57],"sense.":[58],"Depending":[59],"on":[60,91],"complexity":[62],"dimensionality":[64],"scene,":[68],"algorithm":[71],"may":[72],"be":[73],"computationally":[74],"expensive.":[75],"In":[76],"this":[77],"paper,":[78],"we":[79],"propose":[80],"massively":[82],"parallel":[83],"design":[84],"acceleration":[90],"NVIDIA's":[92],"graphics":[93],"processing":[94],"units":[95],"(GPUs).":[96],"Our":[97],"pure":[98],"GPU-based":[99],"implementation":[100,121,162],"includes":[101],"optimal":[103],"use":[104],"page-locked":[107],"host":[108],"memory,":[109],"block":[110],"size,":[111],"number":[114],"registers":[116],"per":[117],"thread.":[118],"proposed":[120],"was":[122],"validated":[123],"terms":[125],"accuracy":[127],"using":[130],"NASA":[132],"AVIRIS":[133],"data.":[135],"benchmark":[137],"with":[138,151],"NVIDIA":[140],"GeForce":[141],"GTX":[142],"580":[143],"Tesla":[145],"K20":[146],"GPUs":[147],"shows":[148],"significant":[149],"speedups":[150],"regards":[152],"optimized":[155],"CPU-based":[156],"serial":[157],"counterpart.":[158],"This":[159],"new":[160],"fast":[161],"demonstrates":[167],"good":[168],"potential":[169],"real-time":[171],"applications.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}