{"id":"https://openalex.org/W2137448824","doi":"https://doi.org/10.1109/lgrs.2009.2026191","title":"Swarm Intelligence Approach to Wavelet Design for Hyperspectral Image Classification","display_name":"Swarm Intelligence Approach to Wavelet Design for Hyperspectral Image Classification","publication_year":2009,"publication_date":"2009-08-11","ids":{"openalex":"https://openalex.org/W2137448824","doi":"https://doi.org/10.1109/lgrs.2009.2026191","mag":"2137448824"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2009.2026191","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2009.2026191","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"},"type":"article","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/A5088653167","display_name":"Abdelhamid Daamouche","orcid":"https://orcid.org/0000-0002-8085-879X"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"A. Daamouche","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","Department of Information Engineering and Computer Science, University of Trento , Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]},{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento , Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021389231","display_name":"Farid Melgani","orcid":"https://orcid.org/0000-0001-9745-3732"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"F. Melgani","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","Department of Information Engineering and Computer Science, University of Trento , Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]},{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento , Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088653167"],"corresponding_institution_ids":["https://openalex.org/I193223587"],"apc_list":null,"apc_paid":null,"fwci":2.6778,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.90977293,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"6","issue":"4","first_page":"825","last_page":"829"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"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":0.9994999766349792,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9979000091552734,"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/wavelet","display_name":"Wavelet","score":0.8644917011260986},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7707827091217041},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6532016396522522},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6425595283508301},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6019827127456665},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.5998179912567139},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5670831799507141},{"id":"https://openalex.org/keywords/lifting-scheme","display_name":"Lifting scheme","score":0.5432438254356384},{"id":"https://openalex.org/keywords/polyphase-system","display_name":"Polyphase system","score":0.5257659554481506},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.46628710627555847},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.4538598358631134},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4458485543727875},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4448874294757843},{"id":"https://openalex.org/keywords/filter-bank","display_name":"Filter bank","score":0.4205024540424347},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3362886905670166},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.31565356254577637},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.27776044607162476},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20406341552734375},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07490429282188416}],"concepts":[{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.8644917011260986},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7707827091217041},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6532016396522522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6425595283508301},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6019827127456665},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.5998179912567139},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5670831799507141},{"id":"https://openalex.org/C199550912","wikidata":"https://www.wikidata.org/wiki/Q3238415","display_name":"Lifting scheme","level":5,"score":0.5432438254356384},{"id":"https://openalex.org/C96157337","wikidata":"https://www.wikidata.org/wiki/Q391639","display_name":"Polyphase system","level":2,"score":0.5257659554481506},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.46628710627555847},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.4538598358631134},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4458485543727875},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4448874294757843},{"id":"https://openalex.org/C100515483","wikidata":"https://www.wikidata.org/wiki/Q3268235","display_name":"Filter bank","level":3,"score":0.4205024540424347},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3362886905670166},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.31565356254577637},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27776044607162476},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20406341552734375},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07490429282188416},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lgrs.2009.2026191","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2009.2026191","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"},{"id":"pmh:oai:iris.unitn.it:11572/76938","is_oa":false,"landing_page_url":"http://hdl.handle.net/11572/76938","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1481646516","https://openalex.org/W1658679052","https://openalex.org/W1976426738","https://openalex.org/W2097092275","https://openalex.org/W2098914003","https://openalex.org/W2109074007","https://openalex.org/W2115755118","https://openalex.org/W2121808441","https://openalex.org/W2125654608","https://openalex.org/W2138887644","https://openalex.org/W2145781461","https://openalex.org/W2153534417","https://openalex.org/W2158885819","https://openalex.org/W2799061466","https://openalex.org/W4239875977"],"related_works":["https://openalex.org/W2537414839","https://openalex.org/W1980778204","https://openalex.org/W2199954716","https://openalex.org/W4231678179","https://openalex.org/W2950739756","https://openalex.org/W1588899229","https://openalex.org/W2389244263","https://openalex.org/W1976022598","https://openalex.org/W2370269080","https://openalex.org/W1506615375"],"abstract_inverted_index":{"Wavelets":[0],"are":[1],"known":[2],"to":[3,17],"be":[4],"a":[5,25,34,50,59,74],"valuable":[6],"tool":[7],"for":[8],"analyzing":[9],"hyperspectral":[10,52],"images.":[11],"In":[12],"this":[13],"letter,":[14],"we":[15],"propose":[16],"further":[18],"improve":[19],"their":[20],"performance":[21],"by":[22,49,57],"means":[23],"of":[24,41,62],"novel":[26],"classification-driven":[27],"design":[28,85],"scheme":[29],"that":[30,36,81],"aims":[31],"at":[32],"deriving":[33],"wavelet":[35,64,70,84],"best":[37],"represents":[38],"in":[39,97],"terms":[40],"between-class":[42],"discrimination":[43],"capability":[44],"the":[45,63,69,82,88,93,98],"spectral":[46],"signatures":[47],"conveyed":[48],"given":[51],"image.":[53],"This":[54],"is":[55],"achieved":[56],"adopting":[58],"polyphase":[60],"representation":[61],"filter":[65],"bank":[66],"and":[67],"formulating":[68],"optimization":[71],"problem":[72],"within":[73],"particle-swarm-optimization":[75],"(PSO)":[76],"framework.":[77],"Experimental":[78],"results":[79],"show":[80],"proposed":[83],"method":[86],"outperforms":[87],"popular":[89],"Daubechies":[90],"wavelets":[91],"whatever":[92],"classifier":[94],"type":[95],"adopted":[96],"classification":[99],"process.":[100]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":4},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}