{"id":"https://openalex.org/W2901562115","doi":"https://doi.org/10.1109/igarss.2018.8518370","title":"Spatial-Spectral Graph-Based Nonlinear Embedding Dimensionality Reduction for Hyperspectral Image Classificaiton","display_name":"Spatial-Spectral Graph-Based Nonlinear Embedding Dimensionality Reduction for Hyperspectral Image Classificaiton","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2901562115","doi":"https://doi.org/10.1109/igarss.2018.8518370","mag":"2901562115"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8518370","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518370","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5049776440","display_name":"Xiangrong Zhang","orcid":"https://orcid.org/0000-0003-0379-2042"},"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":"Xiangrong Zhang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010410587","display_name":"Yaru Han","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":false,"raw_author_name":"Yaru Han","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066376249","display_name":"Ning Huyan","orcid":"https://orcid.org/0000-0002-6123-8659"},"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":"Ning Huyan","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100369916","display_name":"Chen Li","orcid":"https://orcid.org/0000-0003-1545-8885"},"institutions":[{"id":"https://openalex.org/I4210149087","display_name":"Xi'an Railway Survey and Design Institute","ror":"https://ror.org/04emf4852","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210149087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Li","raw_affiliation_strings":["Xi'an research institute of surveying and mapping, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an research institute of surveying and mapping, Xi'an, China","institution_ids":["https://openalex.org/I4210149087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045546082","display_name":"Jie Feng","orcid":"https://orcid.org/0000-0002-8032-7542"},"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":"Jie Feng","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006551076","display_name":"Li Gao","orcid":"https://orcid.org/0000-0001-5758-3516"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Gao","raw_affiliation_strings":["School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101457275","display_name":"Xiaoxiao Ma","orcid":"https://orcid.org/0000-0002-4791-8914"},"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":"Xiaoxiao Ma","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8472","last_page":"8475"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9898999929428101,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9420999884605408,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.7568380832672119},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7436493635177612},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6120447516441345},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6090165376663208},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5928961038589478},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5562863349914551},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5354796648025513},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.4832947552204132},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.4611317217350006},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32028377056121826},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.16666704416275024}],"concepts":[{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.7568380832672119},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7436493635177612},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6120447516441345},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6090165376663208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5928961038589478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5562863349914551},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5354796648025513},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.4832947552204132},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.4611317217350006},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32028377056121826},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.16666704416275024}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8518370","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518370","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2024886312","https://openalex.org/W2030629635","https://openalex.org/W2048281487","https://openalex.org/W2063385051","https://openalex.org/W2090826137","https://openalex.org/W2135431554","https://openalex.org/W2305894755","https://openalex.org/W2313529869","https://openalex.org/W2331181944","https://openalex.org/W2345059010","https://openalex.org/W2518045224","https://openalex.org/W3148981562"],"related_works":["https://openalex.org/W2375574759","https://openalex.org/W2383239174","https://openalex.org/W3088634662","https://openalex.org/W2292979300","https://openalex.org/W117517268","https://openalex.org/W2137369096","https://openalex.org/W3162910294","https://openalex.org/W2539700568","https://openalex.org/W2931531042","https://openalex.org/W1489327846"],"abstract_inverted_index":{"Dimensionality":[0],"reduction":[1,106],"(DR)":[2],"is":[3,47,64,92,126,131,148],"one":[4],"of":[5,14,36,53,90,165,181],"the":[6,12,33,40,51,96,120,135,145,152,163,172,176,182],"most":[7],"important":[8],"tasks":[9],"to":[10,31,49,150,157],"improve":[11],"performance":[13,80],"hyperspectral":[15,54],"images":[16],"classification.":[17],"Recently,":[18],"a":[19,58,76,103,116],"sparse":[20],"and":[21,42,56,137],"low-rank":[22],"graph":[23,130,154],"embedding":[24,112,155],"based":[25,65,123],"method":[26,107,174],"(SLGE)":[27],"has":[28],"been":[29],"proposed":[30,102,173],"describe":[32],"intrinsic":[34],"structure":[35],"data":[37,55,142],"combined":[38],"with":[39],"local":[41],"global":[43],"constraint":[44],"simultaneously,":[45],"which":[46,160],"effective":[48],"reduce":[50],"dimension":[52],"obtain":[57],"better":[59],"classification":[60,183],"accuracy.":[61,184],"However,":[62],"SLGE":[63],"on":[66,124,140],"an":[67],"assumption":[68],"that":[69,171],"low-dimensional":[70],"feature":[71],"can":[72],"be":[73],"obtained":[74],"utilizing":[75],"linear":[77],"projection.":[78],"Its":[79],"may":[81],"degrade":[82],"under":[83],"nonlinearly":[84,158],"distributed":[85],"data.":[86,167],"Moreover,":[87],"spatial":[88],"prior":[89],"HSI":[91],"not":[93],"considered":[94],"in":[95,179],"framework.":[97],"In":[98],"this":[99],"paper,":[100],"we":[101],"novel":[104],"dimensionality":[105],"named":[108],"spatial-spectral":[109,129],"graph-based":[110],"non-linear":[111],"(SSGNE).":[113],"To":[114],"generate":[115],"new":[117],"graph-trained":[118,141],"data,":[119],"segmentation":[121],"strategy":[122],"superpixel":[125],"adopted.":[127],"The":[128],"constructed":[132],"by":[133],"constraining":[134],"sparsity":[136],"low-rankness":[138],"simultaneously":[139],"set.":[143],"Finally,":[144],"kernel":[146],"trick":[147],"adopted":[149],"extend":[151],"general":[153],"framework":[156],"space,":[159],"fully":[161],"considers":[162],"complexity":[164],"real":[166],"Experimental":[168],"results":[169],"show":[170],"outperforms":[175],"state-of-the-art":[177],"methods":[178],"terms":[180]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}