{"id":"https://openalex.org/W2012508386","doi":"https://doi.org/10.1109/tgrs.2015.2418203","title":"Dimensionality Reduction of Hyperspectral Images With Sparse Discriminant Embedding","display_name":"Dimensionality Reduction of Hyperspectral Images With Sparse Discriminant Embedding","publication_year":2015,"publication_date":"2015-04-21","ids":{"openalex":"https://openalex.org/W2012508386","doi":"https://doi.org/10.1109/tgrs.2015.2418203","mag":"2012508386"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2015.2418203","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2015.2418203","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101829389","display_name":"Hong Huang","orcid":"https://orcid.org/0000-0002-7377-3077"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Huang","raw_affiliation_strings":["Key Laboratory on Opto-electronic Technique and Systems, Ministry of Education, Chongqing University, Chongqing, China","Key Lab. on Opto-Electron. Tech. & Syst., Chongqing Univ., Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory on Opto-electronic Technique and Systems, Ministry of Education, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"Key Lab. on Opto-Electron. Tech. & Syst., Chongqing Univ., Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101870407","display_name":"Mei Yang","orcid":"https://orcid.org/0000-0003-0367-2841"},"institutions":[{"id":"https://openalex.org/I4210135349","display_name":"Shanghai Institute of Optics and Fine Mechanics","ror":"https://ror.org/03g897070","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210135349"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mei Yang","raw_affiliation_strings":["Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, China","Shanghai Inst. of Opt. & Fine Mech., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, China","institution_ids":["https://openalex.org/I4210135349"]},{"raw_affiliation_string":"Shanghai Inst. of Opt. & Fine Mech., Shanghai, China","institution_ids":["https://openalex.org/I4210135349"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.436,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.97232462,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"53","issue":"9","first_page":"5160","last_page":"5169"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.986299991607666,"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":0.8322064280509949},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.7790123224258423},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7402370572090149},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.7064825892448425},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6361480355262756},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6291424036026001},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5643067359924316},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.5607882738113403},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5521029829978943},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.548871636390686},{"id":"https://openalex.org/keywords/imaging-spectrometer","display_name":"Imaging spectrometer","score":0.4998462200164795},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4679521322250366},{"id":"https://openalex.org/keywords/spectrometer","display_name":"Spectrometer","score":0.3431149125099182},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32603543996810913},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10377469658851624},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.09676414728164673}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8322064280509949},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.7790123224258423},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7402370572090149},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.7064825892448425},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6361480355262756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6291424036026001},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5643067359924316},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.5607882738113403},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5521029829978943},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.548871636390686},{"id":"https://openalex.org/C183852935","wikidata":"https://www.wikidata.org/wiki/Q6002848","display_name":"Imaging spectrometer","level":3,"score":0.4998462200164795},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4679521322250366},{"id":"https://openalex.org/C33390570","wikidata":"https://www.wikidata.org/wiki/Q188463","display_name":"Spectrometer","level":2,"score":0.3431149125099182},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32603543996810913},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10377469658851624},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.09676414728164673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2015.2418203","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2015.2418203","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"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G102790734","display_name":null,"funder_award_id":"41371338","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2840683992","display_name":null,"funder_award_id":"XM2012001","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G4302507078","display_name":null,"funder_award_id":"61101168","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4833151781","display_name":null,"funder_award_id":"106112013CDJZR125501","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G530586047","display_name":null,"funder_award_id":"2013T60837","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G5774913599","display_name":null,"funder_award_id":"1061120131204","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8258200981","display_name":null,"funder_award_id":"2012M511906","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"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":40,"referenced_works":["https://openalex.org/W1904464160","https://openalex.org/W1990075722","https://openalex.org/W1996375822","https://openalex.org/W2001141328","https://openalex.org/W2005106632","https://openalex.org/W2007653704","https://openalex.org/W2019338222","https://openalex.org/W2037034832","https://openalex.org/W2040812261","https://openalex.org/W2048281487","https://openalex.org/W2048832139","https://openalex.org/W2053186076","https://openalex.org/W2059497048","https://openalex.org/W2070127246","https://openalex.org/W2070424424","https://openalex.org/W2090826137","https://openalex.org/W2097308346","https://openalex.org/W2097915756","https://openalex.org/W2100975942","https://openalex.org/W2103250033","https://openalex.org/W2109531142","https://openalex.org/W2111282613","https://openalex.org/W2112589365","https://openalex.org/W2117553576","https://openalex.org/W2130796525","https://openalex.org/W2130835014","https://openalex.org/W2136540140","https://openalex.org/W2143343993","https://openalex.org/W2146047955","https://openalex.org/W2153409933","https://openalex.org/W2171171329","https://openalex.org/W2171500336","https://openalex.org/W2171566342","https://openalex.org/W3014771378","https://openalex.org/W3120421331","https://openalex.org/W3148981562","https://openalex.org/W6675955514","https://openalex.org/W6676189307","https://openalex.org/W6681521150","https://openalex.org/W6684897833"],"related_works":["https://openalex.org/W2113974028","https://openalex.org/W2380406357","https://openalex.org/W4214747999","https://openalex.org/W198500362","https://openalex.org/W1995428479","https://openalex.org/W2151826682","https://openalex.org/W2750036380","https://openalex.org/W2048060766","https://openalex.org/W2375837050","https://openalex.org/W1703430188"],"abstract_inverted_index":{"Sparse":[0],"manifold":[1],"learning":[2],"has":[3,15],"drawn":[4],"more":[5,7],"and":[6,10,71,96,119],"attentions":[8],"recently,":[9],"sparsity":[11,72],"preserving":[12],"projections":[13],"(SPP)":[14],"been":[16],"proposed,":[17],"which":[18,51],"inherits":[19],"the":[20,30,34,65,78,91,97,114,130,133],"advantages":[21],"of":[22,37,67,94,100,132],"sparse":[23,31,54,79],"reconstruction.":[24],"However,":[25],"SPP":[26],"only":[27,76],"focuses":[28],"on":[29,108],"structure,":[32],"ignoring":[33],"discriminant":[35,55],"information":[36],"labeled":[38],"samples.":[39],"In":[40],"this":[41],"paper,":[42],"we":[43],"proposed":[44,134],"a":[45],"new":[46],"supervised":[47],"dimensionality":[48],"reduction":[49],"method,":[50],"is":[52,102],"called":[53],"embedding":[56],"(SDE),":[57],"for":[58],"hyperspectral":[59],"image":[60],"(HSI)":[61],"classification.":[62],"SDE":[63,101,135],"utilizes":[64],"merits":[66],"both":[68],"intermanifold":[69,92],"structure":[70],"property.":[73],"It":[74],"not":[75],"preserves":[77],"reconstructive":[80],"relations":[81],"through":[82],"l":[83],"<sub":[84],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[85],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[86],"-graph":[87],"but":[88],"also":[89],"enhances":[90],"separability":[93],"data,":[95],"discriminating":[98],"power":[99],"further":[103],"improved":[104],"than":[105],"SPP.":[106],"Experiments":[107],"two":[109],"real":[110],"HSIs":[111],"collected":[112],"by":[113],"Airborne":[115],"Visible/Infrared":[116],"Imaging":[117,123],"Spectrometer":[118,124],"Reflective":[120],"Optics":[121],"System":[122],"sensors":[125],"are":[126],"performed":[127],"to":[128],"demonstrate":[129],"effectiveness":[131],"method.":[136]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
