{"id":"https://openalex.org/W2086505477","doi":"https://doi.org/10.1109/lgrs.2014.2362512","title":"Classification of Hyperspectral Image Based on Sparse Representation in Tangent Space","display_name":"Classification of Hyperspectral Image Based on Sparse Representation in Tangent Space","publication_year":2014,"publication_date":"2014-10-17","ids":{"openalex":"https://openalex.org/W2086505477","doi":"https://doi.org/10.1109/lgrs.2014.2362512","mag":"2086505477"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2014.2362512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2014.2362512","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/A5049353242","display_name":"Ding Ni","orcid":"https://orcid.org/0000-0003-1933-8768"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ding Ni","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Dept. of Electron. Eng., TsingHua Univ., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Dept. of Electron. Eng., TsingHua Univ., Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075551339","display_name":"Hongbing Ma","orcid":"https://orcid.org/0000-0002-1785-4024"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongbing Ma","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Dept. of Electron. Eng., TsingHua Univ., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Dept. of Electron. Eng., TsingHua Univ., Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5049353242"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":4.4807,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.94940171,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"12","issue":"4","first_page":"786","last_page":"790"},"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":0.9939000010490417,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9890000224113464,"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/tangent-space","display_name":"Tangent space","score":0.8454835414886475},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.6774744391441345},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.6569007635116577},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6096462607383728},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6082820892333984},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5463708639144897},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.5314285755157471},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5262845158576965},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5093146562576294},{"id":"https://openalex.org/keywords/tangent","display_name":"Tangent","score":0.46354812383651733},{"id":"https://openalex.org/keywords/manifold-alignment","display_name":"Manifold alignment","score":0.4390912353992462},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4355270564556122},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42992857098579407},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.15107914805412292},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.0881328284740448},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08246743679046631}],"concepts":[{"id":"https://openalex.org/C157157409","wikidata":"https://www.wikidata.org/wiki/Q909601","display_name":"Tangent space","level":2,"score":0.8454835414886475},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.6774744391441345},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.6569007635116577},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6096462607383728},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6082820892333984},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5463708639144897},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.5314285755157471},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5262845158576965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5093146562576294},{"id":"https://openalex.org/C138187205","wikidata":"https://www.wikidata.org/wiki/Q131251","display_name":"Tangent","level":2,"score":0.46354812383651733},{"id":"https://openalex.org/C153120616","wikidata":"https://www.wikidata.org/wiki/Q17068315","display_name":"Manifold alignment","level":4,"score":0.4390912353992462},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4355270564556122},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42992857098579407},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.15107914805412292},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0881328284740448},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08246743679046631},{"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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":1,"locations":[{"id":"doi:10.1109/lgrs.2014.2362512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2014.2362512","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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1979158807","https://openalex.org/W1996939238","https://openalex.org/W1997565609","https://openalex.org/W2048281487","https://openalex.org/W2052575990","https://openalex.org/W2054502547","https://openalex.org/W2060312700","https://openalex.org/W2063385051","https://openalex.org/W2097915756","https://openalex.org/W2098057602","https://openalex.org/W2111282613","https://openalex.org/W2113606819","https://openalex.org/W2122518098","https://openalex.org/W2129812935","https://openalex.org/W2144348684","https://openalex.org/W2157872906","https://openalex.org/W2160059488","https://openalex.org/W2164330327","https://openalex.org/W2167905668","https://openalex.org/W2171566342","https://openalex.org/W6676903177","https://openalex.org/W6683194942"],"related_works":["https://openalex.org/W3049101726","https://openalex.org/W2013051270","https://openalex.org/W2112685067","https://openalex.org/W138920633","https://openalex.org/W2013450515","https://openalex.org/W2540547653","https://openalex.org/W3011406170","https://openalex.org/W2158867000","https://openalex.org/W3118429133","https://openalex.org/W2042880460"],"abstract_inverted_index":{"In":[0,22],"many":[1],"real-world":[2],"problems,":[3],"data":[4],"always":[5],"lie":[6],"in":[7,63,111],"a":[8,27],"low-dimensional":[9],"manifold.":[10,39],"Exploiting":[11],"the":[12,17,37,42,47,54,58,75,79,84,88,99,126,134],"manifold":[13,49,86],"can":[14],"greatly":[15],"enhance":[16],"discrimination":[18],"between":[19],"different":[20],"categories.":[21],"this":[23],"letter,":[24],"we":[25],"propose":[26],"classification":[28,70,135],"framework":[29],"based":[30],"on":[31],"sparse":[32,61],"representation":[33,62],"to":[34,45,106],"directly":[35],"exploit":[36],"underlying":[38],"Specifically,":[40],"using":[41],"tangent":[43,64,92],"plane":[44,93],"approximate":[46],"local":[48,85],"of":[50,87,108,136],"each":[51],"test":[52,76,89],"sample,":[53],"proposed":[55,80,127],"method":[56,81],"classifies":[57],"sample":[59,77,90,100],"by":[60,91],"space.":[65],"Unlike":[66],"several":[67,130],"existing":[68],"sparse-representation-based":[69],"methods,":[71],"which":[72],"sparsely":[73,82],"represent":[74],"itself,":[78],"represents":[83],"approximation.":[94],"Therefore,":[95],"it":[96],"goes":[97],"beyond":[98],"itself":[101],"and":[102,119],"is":[103],"more":[104],"robust":[105],"kinds":[107],"variations":[109],"confronted":[110],"hyperspectral":[112],"image":[113],"(HSI)":[114],"such":[115],"as":[116],"illustration":[117],"differences":[118],"spectrum":[120],"mixing.":[121],"Experimental":[122],"results":[123],"show":[124],"that":[125],"algorithm":[128],"outperforms":[129],"state-of-the-art":[131],"methods":[132],"for":[133],"HSI":[137],"with":[138],"limited":[139],"training":[140],"samples.":[141]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
