{"id":"https://openalex.org/W2756432460","doi":"https://doi.org/10.1109/lgrs.2017.2743018","title":"Weighted Low-Rank Representation-Based Dimension Reduction for Hyperspectral Image Classification","display_name":"Weighted Low-Rank Representation-Based Dimension Reduction for Hyperspectral Image Classification","publication_year":2017,"publication_date":"2017-09-14","ids":{"openalex":"https://openalex.org/W2756432460","doi":"https://doi.org/10.1109/lgrs.2017.2743018","mag":"2756432460"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2017.2743018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2017.2743018","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5100695218","display_name":"Xiaotao Wang","orcid":null},"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":true,"raw_author_name":"Xiaotao Wang","raw_affiliation_strings":["International Center of Intelligent Perception and Computation, Xidian University, Xi\u2019an, China","School of Computer Science & Technology Xidian University Xi'an China"],"affiliations":[{"raw_affiliation_string":"International Center of Intelligent Perception and Computation, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Computer Science & Technology Xidian University Xi'an China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100453075","display_name":"Fang Liu","orcid":"https://orcid.org/0000-0002-5669-9354"},"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":"Fang Liu","raw_affiliation_strings":["International Center of Intelligent Perception and Computation, Xidian University, Xi\u2019an, China","School of Computer Science & Technology Xidian University Xi'an China"],"affiliations":[{"raw_affiliation_string":"International Center of Intelligent Perception and Computation, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Computer Science & Technology Xidian University Xi'an China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100695218"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":1.6389,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.87175573,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"14","issue":"11","first_page":"1938","last_page":"1942"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9918000102043152,"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":0.9908999800682068,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.758348822593689},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7479970455169678},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.7315759658813477},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.7033656239509583},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.652772068977356},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6304196119308472},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.5736954212188721},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5141487717628479},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5082570910453796},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5042451620101929},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5031563639640808},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4114038944244385}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.758348822593689},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7479970455169678},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.7315759658813477},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.7033656239509583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.652772068977356},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6304196119308472},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.5736954212188721},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5141487717628479},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5082570910453796},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5042451620101929},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5031563639640808},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4114038944244385},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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":1,"locations":[{"id":"doi:10.1109/lgrs.2017.2743018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2017.2743018","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1525778528","display_name":null,"funder_award_id":"61473215","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2559168354","display_name":null,"funder_award_id":"91438201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5736573164","display_name":null,"funder_award_id":"61472306","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7752695167","display_name":null,"funder_award_id":"91438103","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"},{"id":"https://openalex.org/F4320322874","display_name":"Universit\u00e0 degli Studi di Pavia","ror":"https://ror.org/00s6t1f81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W79405465","https://openalex.org/W1490524447","https://openalex.org/W1980061733","https://openalex.org/W1997201895","https://openalex.org/W2036872036","https://openalex.org/W2087263574","https://openalex.org/W2103972604","https://openalex.org/W2107799335","https://openalex.org/W2121647436","https://openalex.org/W2131697388","https://openalex.org/W2144151128","https://openalex.org/W2145962650","https://openalex.org/W2151599207","https://openalex.org/W2158703175","https://openalex.org/W2162698522","https://openalex.org/W2262946425","https://openalex.org/W2968437203","https://openalex.org/W6603183647","https://openalex.org/W6767047471"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W2292979300","https://openalex.org/W2794812819","https://openalex.org/W2137369096","https://openalex.org/W2114217318","https://openalex.org/W3147024994","https://openalex.org/W2587881214","https://openalex.org/W3104072235"],"abstract_inverted_index":{"A":[0],"predimension-reduction":[1,153],"algorithm":[2],"that":[3,95],"couples":[4],"weighted":[5,86],"low-rank":[6,27],"representation":[7],"(WLRR)":[8],"with":[9],"a":[10,26,41,54,84,119,149],"skinny":[11],"intrinsic":[12],"mode":[13,132],"functions":[14],"(IMFs)":[15],"dictionary":[16,123],"is":[17,124,137],"proposed":[18,135],"for":[19],"hyperspectral":[20],"image":[21],"(HSI)":[22],"classification.":[23],"It":[24,44],"seeks":[25],"subspace":[28],"to":[29,88,126,157],"solve":[30],"the":[31,48,64,78,90],"performance":[32],"degradation":[33],"issue":[34],"encountered":[35],"by":[36],"linear":[37],"discriminant":[38,116,121],"analysis":[39],"in":[40],"small-sample-size":[42],"situation.":[43],"can":[45,99],"also":[46],"improve":[47],"scatter":[49],"matrix":[50],"estimation":[51],"when":[52,155],"using":[53],"large":[55],"training":[56],"set.":[57],"Unlike":[58],"those":[59],"commonly":[60],"used":[61],"methods,":[62],"e.g.,":[63],"principal":[65],"component":[66],"analysis-based":[67],"ones,":[68],"WLRR":[69,82],"focuses":[70],"on":[71,77,139],"preserving":[72],"more":[73,110,114],"structure":[74,98,111],"information.":[75],"Based":[76],"traditional":[79,159],"LRR":[80],"model,":[81],"introduces":[83],"local":[85,97],"regularization":[87],"characterize":[89],"correlation":[91],"between":[92],"samples":[93],"such":[94],"HSI-specific":[96],"be":[100],"better":[101],"preserved":[102],"as":[103,105],"well":[104],"its":[106],"global":[107],"structure.":[108],"Indeed,":[109],"information":[112],"gives":[113],"additional":[115],"ability.":[117],"Furthermore,":[118],"new":[120],"IMFs":[122],"designed":[125],"enhance":[127],"interclass":[128],"difference":[129],"via":[130],"empirical":[131],"decomposition.":[133],"The":[134],"method":[136],"investigated":[138],"several":[140],"HSI":[141],"data":[142],"sets.":[143],"All":[144],"experimental":[145],"results":[146],"prove":[147],"it":[148],"competitive":[150],"and":[151],"promising":[152],"means":[154],"compared":[156],"other":[158],"techniques.":[160]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
