A New Algorithm for Bilinear Spectral Unmixing of Hyperspectral Images Using Particle Swarm Optimization

Spectral unmixing is an important technique for exploiting hyperspectral data. The presence of nonlinear mixing effects poses an important problem when attempting to provide accurate estimates of the abundance fractions of pure spectral components (endmembers) in a scene. This problem complicates th...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing Jg. 9; H. 12; S. 5776 - 5790
Hauptverfasser:	Luo, Wenfei, Gao, Lianru, Plaza, Antonio, Marinoni, Andrea, Yang, Bin, Zhong, Liang, Gamba, Paolo, Zhang, Bing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.12.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithm design and analysis Algorithms Computational modeling Hyperspectral imaging Linear programming Mixtures Motivation multiobjective optimization (MO) Multiple objective analysis Nonlinearity Optimization Optimization techniques Particle swarm optimization particle swarm optimization (PSO) simplex volume minimization spectral unmixing
ISSN:	1939-1404, 2151-1535
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	Spectral unmixing is an important technique for exploiting hyperspectral data. The presence of nonlinear mixing effects poses an important problem when attempting to provide accurate estimates of the abundance fractions of pure spectral components (endmembers) in a scene. This problem complicates the development of algorithms that can address all types of nonlinear mixtures in the scene. In this paper, we develop a new strategy to simultaneously estimate both the endmember signatures and their corresponding abundances using a biswarm particle swarm optimization (BiPSO) bilinear unmixing technique based on Fan's model. Our main motivation in this paper is to explore the potential of the newly proposed bilinear mixture model based on particle swarm optimization (PSO) for nonlinear spectral unmixing purposes. By taking advantage of the learning mechanism provided by PSO, we embed a multiobjective optimization technique into the algorithm to handle the more complex constraints in simplex volume minimization algorithms for spectral unmixing, thus avoiding limitations due to penalty factors. Our experimental results, conducted using both synthetic and real hyperspectral data, demonstrate that the proposed BiPSO algorithm can outperform other traditional spectral unmixing techniques by accounting for nonlinearities in the mixtures present in the scene.
AbstractList	Spectral unmixing is an important technique for exploiting hyperspectral data. The presence of nonlinear mixing effects poses an important problem when attempting to provide accurate estimates of the abundance fractions of pure spectral components (endmembers) in a scene. This problem complicates the development of algorithms that can address all types of nonlinear mixtures in the scene. In this paper, we develop a new strategy to simultaneously estimate both the endmember signatures and their corresponding abundances using a biswarm particle swarm optimization (BiPSO) bilinear unmixing technique based on Fan's model. Our main motivation in this paper is to explore the potential of the newly proposed bilinear mixture model based on particle swarm optimization (PSO) for nonlinear spectral unmixing purposes. By taking advantage of the learning mechanism provided by PSO, we embed a multiobjective optimization technique into the algorithm to handle the more complex constraints in simplex volume minimization algorithms for spectral unmixing, thus avoiding limitations due to penalty factors. Our experimental results, conducted using both synthetic and real hyperspectral data, demonstrate that the proposed BiPSO algorithm can outperform other traditional spectral unmixing techniques by accounting for nonlinearities in the mixtures present in the scene.
Author	Luo, Wenfei Gamba, Paolo Marinoni, Andrea Zhang, Bing Gao, Lianru Yang, Bin Plaza, Antonio Zhong, Liang
Author_xml	– sequence: 1 givenname: Wenfei surname: Luo fullname: Luo, Wenfei email: luowenfei@m.scnu.edu.cn organization: School of Geographical Science, South China Normal University, Guangzhou, China – sequence: 2 givenname: Lianru surname: Gao fullname: Gao, Lianru email: gaolr@radi.ac.cn organization: Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China – sequence: 3 givenname: Antonio surname: Plaza fullname: Plaza, Antonio email: aplaza@unex.es organization: Department of Technology of Computers and Communications, Escuela Politécnica de Cáceres, University of Extremadura, Badajoz, Spain – sequence: 4 givenname: Andrea surname: Marinoni fullname: Marinoni, Andrea email: andrea.marinoni@unipv.it organization: Dipartimento di Ingegneria Industriale e dell'Informazione, Università degli Studi di Pavia, Pavia, Italy – sequence: 5 givenname: Bin surname: Yang fullname: Yang, Bin email: yangb15@fudan.edu.cn organization: School of Geographical Science, South China Normal University, Guangzhou, China – sequence: 6 givenname: Liang surname: Zhong fullname: Zhong, Liang email: ouly65@hotmail.com organization: Department of Computer and Information Engineering, Guangdong Technical College of Water Resources and Electric Engineering, Guangzhou, China – sequence: 7 givenname: Paolo surname: Gamba fullname: Gamba, Paolo email: paolo.gamba@unipv.it organization: Dipartimento di Ingegneria Industriale e dell'Informazione, Università degli Studi di Pavia, Pavia, Italy – sequence: 8 givenname: Bing surname: Zhang fullname: Zhang, Bing email: zb@radi.ac.cn organization: Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China
BookMark	eNqFkMtOAjEUhhuDiYA-AZsmrgd7mZbpEokKhogRWE9K5wyUzM12COLTywi6cOPqLP7zncvXQa2iLAChHiV9Som6e54vhm_zPiNU9pkkLIrYBWozKmhABRct1KaKq4CGJLxCHe-3hEg2ULyNNkP8Ans8zNals_Umx2np8L3NbAHa4XkFpnY6w8sitx-2WOMyxeNDBc7_JJNcr8HjpW_SV-1qazLA8712OZ5Vtc3tp65tWVyjy1RnHm7OtYuWjw-L0TiYzp4mo-E0MDxkdTDgSiQgJYsSTiLJE0MVAQ2hZoIyLuRKG7kyJtE6TUIBoFNuKE2NEESlCedddHuaW7nyfQe-jrflzhXHlTGNwoHkgoimS526jCu9d5DGxtbfdx6fsllMSdyIjU9i40ZsfBZ7ZPkftnI21-7wD9U7URYAfomBkIrQkH8BVZ-Idg
CODEN	IJSTHZ
CitedBy_id	crossref_primary_10_3390_rs9060558 crossref_primary_10_1109_TGRS_2018_2815044 crossref_primary_10_1016_j_infrared_2022_104170 crossref_primary_10_1109_TGRS_2020_2988519 crossref_primary_10_1109_TGRS_2023_3341473 crossref_primary_10_3390_rs13112132 crossref_primary_10_1109_TGRS_2021_3135571 crossref_primary_10_1109_TGRS_2018_2842707 crossref_primary_10_1109_TGRS_2017_2753847 crossref_primary_10_1016_j_compag_2018_07_003 crossref_primary_10_1016_j_compeleceng_2021_107199 crossref_primary_10_1109_JSTARS_2017_2782324 crossref_primary_10_3390_rs10050801 crossref_primary_10_1109_TGRS_2019_2899826 crossref_primary_10_1080_01431161_2024_2320181 crossref_primary_10_1109_TGRS_2019_2903875 crossref_primary_10_1080_01431161_2018_1508912 crossref_primary_10_1109_MGRS_2022_3145854
Cites_doi	10.1016/j.ipl.2006.10.005 10.4095/219526 10.1109/CEC.2005.1554670 10.1109/TGRS.2011.2131145 10.1109/TSP.2012.2222390 10.1109/JSTARS.2012.2194696 10.1186/1687-6180-2012-54 10.1109/JSTARS.2015.2427517 10.1017/CBO9780511804441 10.1016/j.eswa.2010.08.009 10.1109/MHS.1995.494215 10.1109/TEVC.2007.902851 10.1155/2008/685175 10.1088/0266-5611/25/12/123003 10.1109/TGRS.2014.2319337 10.1109/TGRS.2010.2098414 10.1109/JSTARS.2014.2328872 10.1109/TIP.2012.2187668 10.1017/CBO9780511524998 10.1109/WHISPERS.2011.6080928 10.1002/9780470512517.part4 10.1109/TEVC.2008.2009032 10.1109/LGRS.2007.895727 10.1109/TGRS.2005.844293 10.1109/TGRS.2014.2336858 10.1007/978-0-387-74759-0_157 10.1109/TEVC.2006.886448 10.1109/JSTSP.2015.2416693 10.1109/MSP.2013.2279731 10.1117/12.366289 10.1109/TIP.2014.2314022 10.1109/LGRS.2010.2049334 10.1007/s11721-008-0021-5 10.1109/TEVC.2010.2093582 10.1109/36.297973 10.1109/IGARSS.2008.4779330 10.1007/978-1-4419-9170-6_2 10.1109/MSP.2013.2279274 10.1109/TEVC.2004.826069 10.1109/TGRS.2004.835299 10.1109/MLSP.2009.5306262 10.1109/TGRS.2013.2251349 10.1109/TGRS.2006.888466 10.1109/TSMCB.2009.2015054 10.1080/01431160802558659 10.1007/s11721-007-0002-0 10.1109/LGRS.2013.2278993 10.1109/TCYB.2014.2334692 10.1109/WHISPERS.2009.5289072 10.1109/TEVC.2007.896686 10.1109/IGARSS.2007.4423736 10.1515/9781400841059 10.1109/JSTARS.2014.2320576 10.1109/TGRS.2013.2242475 10.1109/JSTARS.2014.2360888 10.1109/36.911111 10.1109/TPWRS.2002.807051
ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2016
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2016
DBID	97E RIA RIE AAYXX CITATION 7UA 8FD C1K F1W FR3 H8D H96 KR7 L.G L7M
DOI	10.1109/JSTARS.2016.2602882
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Water Resources Abstracts Technology Research Database Environmental Sciences and Pollution Management ASFA: Aquatic Sciences and Fisheries Abstracts Engineering Research Database Aerospace Database Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources Civil Engineering Abstracts Aquatic Science & Fisheries Abstracts (ASFA) Professional Advanced Technologies Database with Aerospace
DatabaseTitle	CrossRef Aerospace Database Civil Engineering Abstracts Aquatic Science & Fisheries Abstracts (ASFA) Professional Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources Technology Research Database ASFA: Aquatic Sciences and Fisheries Abstracts Engineering Research Database Advanced Technologies Database with Aerospace Water Resources Abstracts Environmental Sciences and Pollution Management
DatabaseTitleList	Aerospace Database
Database_xml	– sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Geology
EISSN	2151-1535
EndPage	5790
ExternalDocumentID	10_1109_JSTARS_2016_2602882 7569014
Genre	orig-research
GrantInformation_xml	– fundername: Key Research Program of the Chinese Academy of Sciences grantid: KZZD-EW-TZ-18 funderid: 10.13039/501100002367 – fundername: National Natural Science Foundation of China grantid: 41571349; 41325004; 61673184; 40901232 funderid: 10.13039/501100001809 – fundername: Major Special Project–the China High-Resolution Earth Observation System
GroupedDBID	0R~ 29I 4.4 5GY 5VS 6IK 97E AAFWJ AAJGR AASAJ AAWTH ABAZT ABVLG ACIWK AENEX AETIX AFPKN AFRAH AGSQL ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ DU5 EBS EJD ESBDL GROUPED_DOAJ HZ~ IFIPE IPLJI JAVBF M43 O9- OCL OK1 RIA RIE RNS AAYXX CITATION 7UA 8FD C1K F1W FR3 H8D H96 KR7 L.G L7M RIG
ID	FETCH-LOGICAL-c342t-7395de6628d30863dc190eae4a2512356bac6bccdaafd45eeaf3c11fc5509fd33
IEDL.DBID	RIE
ISICitedReferencesCount	20
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000391468900021&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1939-1404
IngestDate	Fri Jul 25 10:40:00 EDT 2025 Sat Nov 29 04:50:55 EST 2025 Tue Nov 18 22:33:10 EST 2025 Wed Aug 27 02:50:28 EDT 2025
IsDoiOpenAccess	false
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	12
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c342t-7395de6628d30863dc190eae4a2512356bac6bccdaafd45eeaf3c11fc5509fd33
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
OpenAccessLink	https://www.openaccessrepository.it/record/102919
PQID	1847635053
PQPubID	75722
PageCount	15
ParticipantIDs	crossref_primary_10_1109_JSTARS_2016_2602882 ieee_primary_7569014 crossref_citationtrail_10_1109_JSTARS_2016_2602882 proquest_journals_1847635053
PublicationCentury	2000
PublicationDate	2016-Dec. 2016-12-00 20161201
PublicationDateYYYYMMDD	2016-12-01
PublicationDate_xml	– month: 12 year: 2016 text: 2016-Dec.
PublicationDecade	2010
PublicationPlace	Piscataway
PublicationPlace_xml	– name: Piscataway
PublicationTitle	IEEE journal of selected topics in applied earth observations and remote sensing
PublicationTitleAbbrev	JSTARS
PublicationYear	2016
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref13 ref56 ref12 ref59 ref15 ref58 ref14 ref52 ref11 ref10 ref17 ref16 ref19 ref18 winter (ref4) 0; 3753 ref51 ref50 bonnans (ref53) 2006 ref46 ref45 ref48 ref47 ref42 ref41 ref44 ruszczynski (ref54) 2006 ref43 ref49 ref8 ref7 ref9 ref3 ref6 ref5 ref40 (ref66) 2006 ref35 ref34 (ref63) 2007 vanden bergh (ref57) 2001 ref36 ref31 ref30 ref33 ref32 ref1 ref39 boardman (ref2) 0; 1 engelbrecht (ref62) 2005 van den bergh (ref38) 2001 ref24 ref23 ref26 ref25 ref64 ref20 ref22 ref65 ref21 ratnaweera (ref61) 0 ref28 ref27 ref29 rebennack (ref55) 2008 ref60 williams (ref37) 1993
References_xml	– ident: ref56 doi: 10.1016/j.ipl.2006.10.005 – ident: ref3 doi: 10.4095/219526 – ident: ref42 doi: 10.1109/CEC.2005.1554670 – ident: ref28 doi: 10.1109/TGRS.2011.2131145 – ident: ref21 doi: 10.1109/TSP.2012.2222390 – ident: ref1 doi: 10.1109/JSTARS.2012.2194696 – ident: ref32 doi: 10.1186/1687-6180-2012-54 – ident: ref23 doi: 10.1109/JSTARS.2015.2427517 – ident: ref64 doi: 10.1017/CBO9780511804441 – ident: ref52 doi: 10.1016/j.eswa.2010.08.009 – ident: ref36 doi: 10.1109/MHS.1995.494215 – ident: ref48 doi: 10.1109/TEVC.2007.902851 – ident: ref44 doi: 10.1155/2008/685175 – ident: ref40 doi: 10.1088/0266-5611/25/12/123003 – ident: ref29 doi: 10.1109/TGRS.2014.2319337 – ident: ref17 doi: 10.1109/TGRS.2010.2098414 – ident: ref35 doi: 10.1109/JSTARS.2014.2328872 – ident: ref19 doi: 10.1109/TIP.2012.2187668 – ident: ref14 doi: 10.1017/CBO9780511524998 – ident: ref34 doi: 10.1109/WHISPERS.2011.6080928 – year: 2007 ident: ref63 – year: 2005 ident: ref62 article-title: Part III particle swarm optimization publication-title: Fundamentals Comput Swarm Intell – ident: ref27 doi: 10.1002/9780470512517.part4 – year: 2006 ident: ref53 publication-title: Numerical Optimization Theoretical and Practical Aspects – ident: ref46 doi: 10.1109/TEVC.2008.2009032 – ident: ref9 doi: 10.1109/LGRS.2007.895727 – ident: ref5 doi: 10.1109/TGRS.2005.844293 – ident: ref24 doi: 10.1109/TGRS.2014.2336858 – start-page: 890 year: 2008 ident: ref55 article-title: Ellipsoid method publication-title: Encyclopedia Optim doi: 10.1007/978-0-387-74759-0_157 – ident: ref43 doi: 10.1109/TEVC.2006.886448 – ident: ref65 doi: 10.1109/JSTSP.2015.2416693 – ident: ref6 doi: 10.1109/MSP.2013.2279731 – volume: 3753 start-page: 266 year: 0 ident: ref4 article-title: N-FINDR: An algorithm for fast autonomous spectral endmember determination in hyperspectral data publication-title: Proc SPIE Conf Imag Spectrometry V doi: 10.1117/12.366289 – year: 1993 ident: ref37 article-title: Narrow-band analyzer – start-page: 264 year: 0 ident: ref61 article-title: Particle swarm optimization with self-adaptive acceleration coefficients publication-title: Proc 1st Int Conf Fuzzy Syst Knowl Discovery – ident: ref26 doi: 10.1109/TIP.2014.2314022 – ident: ref15 doi: 10.1109/LGRS.2010.2049334 – ident: ref41 doi: 10.1007/s11721-008-0021-5 – ident: ref47 doi: 10.1109/TEVC.2010.2093582 – ident: ref7 doi: 10.1109/36.297973 – ident: ref11 doi: 10.1109/IGARSS.2008.4779330 – volume: 1 start-page: 23 year: 0 ident: ref2 article-title: Mapping target signatures via partial unmixing of AVIRIS data publication-title: Proc 5th JPL Airborne Earth Sci Workshop – ident: ref59 doi: 10.1007/978-1-4419-9170-6_2 – ident: ref33 doi: 10.1109/MSP.2013.2279274 – year: 2001 ident: ref38 article-title: An analysis of particle swarm optimizers – ident: ref50 doi: 10.1109/TEVC.2004.826069 – start-page: 111 year: 2001 ident: ref57 article-title: An analysis of particle swarm optimizers – ident: ref8 doi: 10.1109/TGRS.2004.835299 – year: 2006 ident: ref66 – ident: ref31 doi: 10.1109/MLSP.2009.5306262 – ident: ref22 doi: 10.1109/TGRS.2013.2251349 – ident: ref10 doi: 10.1109/TGRS.2006.888466 – ident: ref51 doi: 10.1109/TSMCB.2009.2015054 – ident: ref16 doi: 10.1080/01431160802558659 – ident: ref39 doi: 10.1007/s11721-007-0002-0 – ident: ref25 doi: 10.1109/LGRS.2013.2278993 – ident: ref49 doi: 10.1109/TCYB.2014.2334692 – ident: ref12 doi: 10.1109/WHISPERS.2009.5289072 – ident: ref45 doi: 10.1109/TEVC.2007.896686 – ident: ref20 doi: 10.1109/IGARSS.2007.4423736 – year: 2006 ident: ref54 publication-title: Nonlinear Optimization doi: 10.1515/9781400841059 – ident: ref13 doi: 10.1109/JSTARS.2014.2320576 – ident: ref18 doi: 10.1109/TGRS.2013.2242475 – ident: ref30 doi: 10.1109/JSTARS.2014.2360888 – ident: ref58 doi: 10.1109/36.911111 – ident: ref60 doi: 10.1109/TPWRS.2002.807051
SSID	ssj0062793
Score	2.2343743
Snippet	Spectral unmixing is an important technique for exploiting hyperspectral data. The presence of nonlinear mixing effects poses an important problem when...
SourceID	proquest crossref ieee
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	5776
SubjectTerms	Algorithm design and analysis Algorithms Computational modeling Hyperspectral imaging Linear programming Mixtures Motivation multiobjective optimization (MO) Multiple objective analysis Nonlinearity Optimization Optimization techniques Particle swarm optimization particle swarm optimization (PSO) simplex volume minimization spectral unmixing
Title	A New Algorithm for Bilinear Spectral Unmixing of Hyperspectral Images Using Particle Swarm Optimization
URI	https://ieeexplore.ieee.org/document/7569014 https://www.proquest.com/docview/1847635053
Volume	9
WOSCitedRecordID	wos000391468900021&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 2151-1535 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0062793 issn: 1939-1404 databaseCode: RIE dateStart: 20080101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1ZS8QwEB5UFHzxWsX1Ig8-Wu2RJs3jKl4gKuqCbyVNUndhuyt7ePx7M2l2QRTBt0KTUPpN5khmvgE41FwJLVQaRJSbgMrIbimGXIRpoVVUlCaLXKHwDb-9zZ6fxf0cHM1qYYwxLvnMHOOju8vXAzXBo7ITnmL7JDoP85yzulZrqnVZzB3BrvVHRICUMZ5hKArFiRXx1sMjpnGxY-u-x1kWf7NCrq3KD13sDMzF6v8-bQ1WvCNJWjXy6zBn-huwdOka9X42oNMiVn-RVu9lYMP_TkWsc0pOu-hUyiHBrvN4xEHa_ar7Ya0XGZTkyoakdeUlvrmurKYZEZdSQO69gJHHdzmsyJ3VM5Uv4NyE9sX509lV4LsqBCqh8TjAmzltGIszndh4JrGQiNBIQyW6OknKCqlYoZSWstQ0NUaWiYqiUtlYRpQ6SbZgoT_om20goRQaGeppFJeU00JyHmJlq-Qh1SWTTYinfzlXnnIcO1_0chd6hCKvockRmtxD04Sj2aTXmnHj7-ENRGM21APRhL0pnLnflaPcRrPIv2f1zs7vs3ZhGdeu01X2YGE8nJh9WFRv4-5oeOAE7guHX9Nr
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3dT9swED91ZRN7GYyCKAPmhz2SNh9OHD8WBLRa6RAfUt8ix3agUtOitGzjv8fnuJWmTZN4ixRbjvI734d99zuAb4pJrriMvYAy7VERmC2VIBdhnCsZ5IVOA1soPGSjUToe8-sGnKxrYbTWNvlMd_DR3uWruXzGo7Iui7F9En0HGzGloV9Xa630bhIyS7FrPBLuIWmM4xgKfN41Qt67ucVErqRjHPgwTcM_7JBtrPKXNrYm5mLrbR-3DZ-cK0l6NfafoaFnO_Dh0rbqfWnBY48YDUZ604d5NVk-lsS4p-R0gm6lqAj2ncdDDnI_Kye_jf0i84L0TVBa117im0FpdM2C2KQCcu1EjNz-ElVJfhhNU7oSzl24vzi_O-t7rq-CJyMaLj28m1M6ScJURSaiiQwo3NdCU4HOThQnuZBJLqUSolA01loUkQyCQppohhcqivagOZvP9D4QX3CFHPU0CAvKaC4Y87G2VTCfqiIRbQhXfzmTjnQce19MMxt8-DyrockQmsxB04aT9aSnmnPj_8NbiMZ6qAOiDYcrODO3LxeZiWeRgc9onoN_z_oKm_27q2E2HIy-f4GPuE6dvHIIzWX1rI_gvfy5nCyqYyt8r67L1rI
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+New+Algorithm+for+Bilinear+Spectral+Unmixing+of+Hyperspectral+Images+Using+Particle+Swarm+Optimization&rft.jtitle=IEEE+journal+of+selected+topics+in+applied+earth+observations+and+remote+sensing&rft.au=Luo%2C+Wenfei&rft.au=Gao%2C+Lianru&rft.au=Plaza%2C+Antonio&rft.au=Marinoni%2C+Andrea&rft.date=2016-12-01&rft.issn=1939-1404&rft.eissn=2151-1535&rft.volume=9&rft.issue=12&rft.spage=5776&rft.epage=5790&rft_id=info:doi/10.1109%2FJSTARS.2016.2602882&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_JSTARS_2016_2602882
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1939-1404&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1939-1404&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1939-1404&client=summon