{"id":"https://openalex.org/W2901888865","doi":"https://doi.org/10.1109/igarss.2018.8518642","title":"Superpixel-Based Nonnegative Tensor Factorization for Hyperspectral Unmixing","display_name":"Superpixel-Based Nonnegative Tensor Factorization for Hyperspectral Unmixing","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2901888865","doi":"https://doi.org/10.1109/igarss.2018.8518642","mag":"2901888865"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8518642","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518642","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":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10072/402413","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033291716","display_name":"Fengchao Xiong","orcid":"https://orcid.org/0000-0002-9753-4919"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fengchao Xiong","raw_affiliation_strings":["College of Computer Science, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057957690","display_name":"Jingzhou Chen","orcid":"https://orcid.org/0000-0001-7297-4945"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingzhou Chen","raw_affiliation_strings":["College of Computer Science, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100781212","display_name":"Jun Zhou","orcid":"https://orcid.org/0000-0001-5822-8233"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jun Zhou","raw_affiliation_strings":["School of Information and Communication Technology, Griffith University, Nathan, Australia"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Technology, Griffith University, Nathan, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059857918","display_name":"Yuntao Qian","orcid":"https://orcid.org/0000-0002-7418-5891"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuntao Qian","raw_affiliation_strings":["College of Computer Science, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5033291716"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":1.2342,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.84288871,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"6392","last_page":"6395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9936000108718872,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.989799976348877,"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":0.9545943737030029},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.7389399409294128},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6263585686683655},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5933778285980225},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5761719346046448},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5662829875946045},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5409238934516907},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5273003578186035},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4758743345737457},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.47059595584869385},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.42437613010406494},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38157305121421814},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21100959181785583},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07869890332221985},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0739118754863739}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9545943737030029},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.7389399409294128},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6263585686683655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5933778285980225},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5761719346046448},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5662829875946045},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5409238934516907},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5273003578186035},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4758743345737457},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47059595584869385},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.42437613010406494},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38157305121421814},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21100959181785583},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07869890332221985},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0739118754863739},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2018.8518642","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518642","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"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/402413","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/402413","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"}],"best_oa_location":{"id":"pmh:oai:research-repository.griffith.edu.au:10072/402413","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/402413","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2063069198","https://openalex.org/W2107120407","https://openalex.org/W2118246710","https://openalex.org/W2135029798","https://openalex.org/W2318512420","https://openalex.org/W2469230926","https://openalex.org/W2551961488","https://openalex.org/W2566771666","https://openalex.org/W2581808969","https://openalex.org/W2591248827","https://openalex.org/W2964179170","https://openalex.org/W6675750237","https://openalex.org/W6680012447"],"related_works":["https://openalex.org/W4281395053","https://openalex.org/W4308269461","https://openalex.org/W2020769413","https://openalex.org/W2766940489","https://openalex.org/W2513087981","https://openalex.org/W2074386779","https://openalex.org/W2127243424","https://openalex.org/W2037504162","https://openalex.org/W2792706544","https://openalex.org/W1568451138"],"abstract_inverted_index":{"Hyperspectral":[0],"unmixing":[1,33],"aims":[2],"at":[3],"decomposing":[4],"a":[5,10,53,88],"hyperspectral":[6,32,97],"image":[7],"(HSI)":[8],"into":[9,109,119],"number":[11],"of":[12,38],"constituted":[13],"materials":[14],"and":[15,29,104,127,163],"associated":[16],"proportions.":[17],"Recently,":[18],"nonnegative":[19,91],"tensor":[20,92,144],"factorization":[21,93,145],"(NTF)":[22],"based":[23],"methods":[24,48],"have":[25],"been":[26],"proved":[27],"effective":[28],"natural":[30],"for":[31,96],"owing":[34],"to":[35,70,142,146],"their":[36],"virtue":[37],"representing":[39,130],"an":[40,50],"HSI":[41,51,115],"without":[42],"any":[43],"information":[44,59,79,103,106,139],"loss.":[45],"However,":[46],"these":[47,84],"take":[49],"as":[52],"whole,":[54],"partly":[55],"ignoring":[56],"the":[57,77,101,114,131,143,148,152,168,172],"local":[58,62,105,132,138],"in":[60,151],"distinct":[61],"regions.":[63],"In":[64,111],"addition,":[65],"HSIs":[66],"are":[67,107],"high":[68],"likely":[69],"be":[71],"disturbed":[72],"by":[73],"various":[74],"noise,":[75],"making":[76],"global":[78,102],"unnecessarily":[80],"reliable.":[81],"To":[82],"alleviate":[83],"drawbacks,":[85],"we":[86],"propose":[87],"superpixel-based":[89],"matrix-vector":[90],"(S-MV-NTF)":[94],"method":[95,170],"unmixing,":[98],"where":[99],"both":[100],"taken":[108],"consideration.":[110],"this":[112],"method,":[113],"is":[116,140],"firstly":[117],"partitioned":[118],"numerous":[120],"superpixels,":[121],"homogeneous":[122],"regions":[123],"with":[124],"adaptive":[125],"sizes":[126],"compact":[128],"boundaries,":[129],"spatial":[133],"structure":[134],"information.":[135],"Then,":[136],"such":[137],"integrated":[141],"make":[147],"pixels":[149],"lying":[150],"same":[153],"superpixel":[154],"share":[155],"similar":[156],"abundances.":[157],"Experimental":[158],"results":[159],"on":[160],"synthetic":[161],"data":[162,165],"real-world":[164],"show":[166],"that":[167],"proposed":[169],"dominates":[171],"state-of-the-art":[173],"methods.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}