{"id":"https://openalex.org/W2606327983","doi":"https://doi.org/10.1109/access.2017.2695616","title":"Two-stage Clustering Technique Based on the Neighboring Union Histogram for Hyperspectral Remote Sensing Images","display_name":"Two-stage Clustering Technique Based on the Neighboring Union Histogram for Hyperspectral Remote Sensing Images","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2606327983","doi":"https://doi.org/10.1109/access.2017.2695616","mag":"2606327983"},"language":"en","primary_location":{"id":"doi:10.1109/access.2017.2695616","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2695616","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2017.2695616","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101483409","display_name":"Wei Yang","orcid":"https://orcid.org/0000-0002-1703-144X"},"institutions":[{"id":"https://openalex.org/I184983240","display_name":"Northeast Normal University","ror":"https://ror.org/02rkvz144","country_code":"CN","type":"education","lineage":["https://openalex.org/I184983240"]},{"id":"https://openalex.org/I202028630","display_name":"Changchun Normal University","ror":"https://ror.org/00cbhey71","country_code":"CN","type":"education","lineage":["https://openalex.org/I202028630"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Yang","raw_affiliation_strings":["College of Computer Science and Technology, Changchun Normal University, Changchun, China","School of Computer Science and Information Technology, Northeast Normal University, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Changchun Normal University, Changchun, China","institution_ids":["https://openalex.org/I202028630"]},{"raw_affiliation_string":"School of Computer Science and Information Technology, Northeast Normal University, Changchun, China","institution_ids":["https://openalex.org/I184983240"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101449197","display_name":"Kun Hou","orcid":"https://orcid.org/0000-0001-9423-3777"},"institutions":[{"id":"https://openalex.org/I184983240","display_name":"Northeast Normal University","ror":"https://ror.org/02rkvz144","country_code":"CN","type":"education","lineage":["https://openalex.org/I184983240"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Hou","raw_affiliation_strings":["School of Computer Science and Information Technology, Northeast Normal University, Changchun, China"],"raw_orcid":"https://orcid.org/0000-0001-9423-3777","affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Technology, Northeast Normal University, Changchun, China","institution_ids":["https://openalex.org/I184983240"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114377956","display_name":"Bo Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I184983240","display_name":"Northeast Normal University","ror":"https://ror.org/02rkvz144","country_code":"CN","type":"education","lineage":["https://openalex.org/I184983240"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Liu","raw_affiliation_strings":["School of Computer Science and Information Technology, Northeast Normal University, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Technology, Northeast Normal University, Changchun, China","institution_ids":["https://openalex.org/I184983240"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101494761","display_name":"Fanhua Yu","orcid":"https://orcid.org/0000-0001-6180-2312"},"institutions":[{"id":"https://openalex.org/I202028630","display_name":"Changchun Normal University","ror":"https://ror.org/00cbhey71","country_code":"CN","type":"education","lineage":["https://openalex.org/I202028630"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fanhua Yu","raw_affiliation_strings":["College of Computer Science and Technology, Changchun Normal University, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Changchun Normal University, Changchun, China","institution_ids":["https://openalex.org/I202028630"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048326379","display_name":"Lei Lin","orcid":"https://orcid.org/0000-0002-1161-8565"},"institutions":[{"id":"https://openalex.org/I2801509770","display_name":"Institut National des Sciences Appliqu\u00e9es de Strasbourg","ror":"https://ror.org/001nta019","country_code":"FR","type":"education","lineage":["https://openalex.org/I2801509770"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Lei Lin","raw_affiliation_strings":["Laboratoire de G\u00e9nie de la Conception, INSA STRASBOURG, Strasbourg, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire de G\u00e9nie de la Conception, INSA STRASBOURG, Strasbourg, France","institution_ids":["https://openalex.org/I2801509770"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101483409"],"corresponding_institution_ids":["https://openalex.org/I184983240","https://openalex.org/I202028630"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":5.1513,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.9579873,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"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":0.998199999332428,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9799000024795532,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.8413386344909668},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7699786424636841},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7485542893409729},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.653039813041687},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6462888717651367},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.640874445438385},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6282621622085571},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3646790087223053},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2465168833732605}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8413386344909668},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7699786424636841},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7485542893409729},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.653039813041687},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6462888717651367},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.640874445438385},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6282621622085571},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3646790087223053},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2465168833732605}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2017.2695616","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2695616","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5b04065e30e8415d9eb11d558e4a2b9a","is_oa":true,"landing_page_url":"https://doaj.org/article/5b04065e30e8415d9eb11d558e4a2b9a","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 5, Pp 5640-5647 (2017)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2017.2695616","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2695616","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.5799999833106995}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309036","display_name":"Purdue University","ror":"https://ror.org/02dqehb95"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1420908056","https://openalex.org/W1972485825","https://openalex.org/W1981367467","https://openalex.org/W1989314352","https://openalex.org/W1992633833","https://openalex.org/W1995716834","https://openalex.org/W2001801361","https://openalex.org/W2018143346","https://openalex.org/W2021047319","https://openalex.org/W2025287381","https://openalex.org/W2031487237","https://openalex.org/W2044337134","https://openalex.org/W2050919167","https://openalex.org/W2051034476","https://openalex.org/W2069231830","https://openalex.org/W2081809992","https://openalex.org/W2086762254","https://openalex.org/W2094510831","https://openalex.org/W2097238823","https://openalex.org/W2102219056","https://openalex.org/W2104269704","https://openalex.org/W2113464037","https://openalex.org/W2114407479","https://openalex.org/W2116767824","https://openalex.org/W2125517209","https://openalex.org/W2127802986","https://openalex.org/W2130627644","https://openalex.org/W2131725398","https://openalex.org/W2138973222","https://openalex.org/W2142009246","https://openalex.org/W2148857973","https://openalex.org/W2149471024","https://openalex.org/W2152709458","https://openalex.org/W2154240401","https://openalex.org/W2158400785","https://openalex.org/W2161528141","https://openalex.org/W2164325628","https://openalex.org/W2164437025","https://openalex.org/W2166056814","https://openalex.org/W2170186417","https://openalex.org/W2171566342","https://openalex.org/W2190646811","https://openalex.org/W2268875920","https://openalex.org/W2507294395"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440","https://openalex.org/W2343470940"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,119],"novel":[4],"unsupervised":[5,153],"classification":[6],"approach":[7,29,125,147],"suited":[8],"to":[9,87,100,127],"hyperspectral":[10,41,164],"remote":[11,165],"sensing":[12,166],"image":[13,42],"data":[14,43],"sets":[15],"that":[16],"uses":[17],"K":[18,84,97],"-means":[19,85,98],"clustering":[20,78,104,109,134],"combined":[21],"with":[22,150],"the":[23,40,49,55,68,82,95,102,107,114,123,137,169,173],"neighboring":[24],"union":[25],"histogram":[26],"(NUH).":[27],"The":[28,111,132,145,155],"is":[30,148],"implemented":[31],"in":[32],"five":[33,151],"main":[34],"steps":[35],"as":[36],"follows:":[37],"1)":[38],"dividing":[39],"intt":[44],"uncorrelated":[45],"groups":[46],"based":[47],"on":[48,158],"correlation":[50],"coefficient":[51],"matrix;":[52],"2)":[53],"extracting":[54],"first":[56],"few":[57],"principal":[58],"component":[59],"analysis":[60],"(PCA)":[61],"components":[62],"from":[63],"each":[64],"group;":[65,72],"3)":[66],"computing":[67],"NUHs":[69],"of":[70,118,140,162,172],"every":[71,89],"4)":[73],"obtaining":[74],"several":[75],"relatively":[76],"rough":[77,103],"results":[79,105,157],"by":[80],"employing":[81],"first-stage":[83],"procedure":[86,99],"classify":[88],"group's":[90],"NUHs;":[91],"and":[92,129],"5)":[93],"using":[94],"second-stage":[96],"refine":[101],"for":[106],"final":[108],"map.":[110],"NUH":[112],"indicates":[113],"regional":[115],"statistical":[116],"features":[117],"point,":[120],"thereby":[121],"making":[122],"proposed":[124,146,174],"insensitive":[126],"noise":[128],"abnormal":[130],"data.":[131],"two-stage":[133],"technique":[135],"improves":[136],"recognition":[138],"rate":[139],"similar":[141],"land":[142],"cover":[143],"classes.":[144],"compared":[149],"other":[152],"methods.":[154],"experimental":[156],"two":[159],"different":[160],"types":[161],"real-world":[163],"images":[167],"validate":[168],"high":[170],"accuracy":[171],"approach.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}