{"id":"https://openalex.org/W3206304544","doi":"https://doi.org/10.1109/igarss47720.2021.9554252","title":"Enhancing Reweighted Low-Rank Representation for Hyperspectral Image Unmixing","display_name":"Enhancing Reweighted Low-Rank Representation for Hyperspectral Image Unmixing","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3206304544","doi":"https://doi.org/10.1109/igarss47720.2021.9554252","mag":"3206304544"},"language":"en","primary_location":{"id":"doi:10.1109/igarss47720.2021.9554252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9554252","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","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/A5013574997","display_name":"Wu-Chao Di","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wu-Chao Di","raw_affiliation_strings":["School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, PR China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029236040","display_name":"Jie Huang","orcid":"https://orcid.org/0000-0002-7684-2533"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Huang","raw_affiliation_strings":["School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, PR China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103104155","display_name":"Jin-Ju Wang","orcid":"https://orcid.org/0000-0002-2515-6971"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin-Ju Wang","raw_affiliation_strings":["School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, PR China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065782725","display_name":"Ting\u2010Zhu Huang","orcid":"https://orcid.org/0000-0001-7766-230X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting-Zhu Huang","raw_affiliation_strings":["School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, PR China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"52","issue":null,"first_page":"3825","last_page":"3828"},"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":0.9991000294685364,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9925000071525574,"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/singular-value","display_name":"Singular value","score":0.8680551052093506},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8258695602416992},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.7624822854995728},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.741754412651062},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6505001783370972},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"Low-rank approximation","score":0.49239909648895264},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.48244649171829224},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4661480188369751},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4603007435798645},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4551756680011749},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4523705542087555},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42911115288734436},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4137399196624756},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4126422703266144},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.12629419565200806},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.0849381685256958}],"concepts":[{"id":"https://openalex.org/C109282560","wikidata":"https://www.wikidata.org/wiki/Q4166054","display_name":"Singular value","level":3,"score":0.8680551052093506},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8258695602416992},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.7624822854995728},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.741754412651062},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6505001783370972},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.49239909648895264},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.48244649171829224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4661480188369751},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4603007435798645},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4551756680011749},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4523705542087555},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42911115288734436},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4137399196624756},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4126422703266144},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.12629419565200806},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0849381685256958},{"id":"https://openalex.org/C25023664","wikidata":"https://www.wikidata.org/wiki/Q1575637","display_name":"Hankel matrix","level":2,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss47720.2021.9554252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9554252","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2751002267","display_name":"\u538b\u7f29\u611f\u77e5\u4e2d\u56fe\u50cf\u91cd\u5efa\u7684\u7a00\u758f\u4f18\u5316\u6a21\u578b\u4e0e\u9ad8\u6027\u80fd\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61772003","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W817041652","https://openalex.org/W1964570608","https://openalex.org/W2027878671","https://openalex.org/W2048695508","https://openalex.org/W2125298866","https://openalex.org/W2163886442","https://openalex.org/W2166864699","https://openalex.org/W2898165830","https://openalex.org/W3099180803"],"related_works":["https://openalex.org/W4319586039","https://openalex.org/W2969683494","https://openalex.org/W4094001","https://openalex.org/W4298234822","https://openalex.org/W2782047334","https://openalex.org/W2163255469","https://openalex.org/W1970576574","https://openalex.org/W3017414697","https://openalex.org/W2522507432","https://openalex.org/W605362495"],"abstract_inverted_index":{"Sparse":[0],"hyperspectral":[1],"unmixing":[2,109,121],"has":[3,27],"attracted":[4],"much":[5],"attention":[6],"in":[7],"recent":[8],"decades.":[9],"Recently,":[10],"the":[11,22,33,36,40,65,72,75,79,116,119],"low-rank":[12],"representation":[13],"provides":[14],"a":[15,60],"new":[16,61],"perspective":[17],"for":[18,64,85],"spatial":[19],"correlation":[20],"and":[21,106,112],"weighted":[23],"nuclear":[24,67],"norm":[25,68],"regularization":[26],"been":[28],"well":[29],"studied":[30],"to":[31,69],"enhance":[32,71],"low-rankness":[34,107],"of":[35,74,78,91,96,118],"abundance":[37,80],"matrix.":[38,81],"However,":[39],"commonly":[41],"used":[42],"weights":[43],"only":[44],"depend":[45],"on":[46],"respective":[47],"singular":[48,52,76,87,93,98],"values,":[49,94],"ignoring":[50],"other":[51],"values'":[53],"information.":[54],"In":[55],"this":[56],"paper,":[57],"we":[58,102],"propose":[59],"weighting":[62],"scheme":[63],"weighed":[66],"further":[70],"sparsity":[73,105],"values":[77],"The":[82],"proposed":[83],"weight":[84],"each":[86],"value":[88,99],"considers":[89],"information":[90],"all":[92],"instead":[95],"particular":[97],"only.":[100],"Then":[101],"refine":[103],"two":[104],"based":[108],"algorithms.":[110,122],"Simulated":[111],"real-data":[113],"experiments":[114],"demonstrate":[115],"effectiveness":[117],"resulting":[120]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
