{"id":"https://openalex.org/W2098837120","doi":"https://doi.org/10.1109/igarss.2008.4779152","title":"Wavelet Packet Tree Pruning Metrics for Hyperspectral Feature Extraction","display_name":"Wavelet Packet Tree Pruning Metrics for Hyperspectral Feature Extraction","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W2098837120","doi":"https://doi.org/10.1109/igarss.2008.4779152","mag":"2098837120"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2008.4779152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2008.4779152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium","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/A5111905438","display_name":"Terrance West","orcid":null},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Terrance R. West","raw_affiliation_strings":["Electrical and Computer Engineering Department, Mississippi State University, MS, USA","Electr. & Comput. Eng. Dept., Mississippi State Univ., Starkville, MS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, Mississippi State University, MS, USA","institution_ids":["https://openalex.org/I99041443"]},{"raw_affiliation_string":"Electr. & Comput. Eng. Dept., Mississippi State Univ., Starkville, MS","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037823063","display_name":"Saurabh Prasad","orcid":"https://orcid.org/0000-0003-3729-9360"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saurabh Prasad","raw_affiliation_strings":["Electrical and Computer Engineering Department, Mississippi State University, MS, USA","Electr. & Comput. Eng. Dept., Mississippi State Univ., Starkville, MS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, Mississippi State University, MS, USA","institution_ids":["https://openalex.org/I99041443"]},{"raw_affiliation_string":"Electr. & Comput. Eng. Dept., Mississippi State Univ., Starkville, MS","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103103246","display_name":"L.M. Bruce","orcid":"https://orcid.org/0000-0002-9380-1143"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lori Mann Bruce","raw_affiliation_strings":["Electrical and Computer Engineering Department, Mississippi State University, MS, USA","Electr. & Comput. Eng. Dept., Mississippi State Univ., Starkville, MS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, Mississippi State University, MS, USA","institution_ids":["https://openalex.org/I99041443"]},{"raw_affiliation_string":"Electr. & Comput. Eng. Dept., Mississippi State Univ., Starkville, MS","institution_ids":["https://openalex.org/I99041443"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99041443"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2303","issue":null,"first_page":"II","last_page":"946"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9977999925613403,"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":0.9977999925613403,"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":0.9883000254631042,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9671000242233276,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7665966749191284},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6695665717124939},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5808666348457336},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5650327205657959},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.552808940410614},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5446746349334717},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.4955326318740845},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4867999255657196},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46231609582901},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.42177021503448486},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.42107611894607544},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3438923954963684},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.33772680163383484}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7665966749191284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6695665717124939},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5808666348457336},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5650327205657959},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.552808940410614},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5446746349334717},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.4955326318740845},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4867999255657196},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46231609582901},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.42177021503448486},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.42107611894607544},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3438923954963684},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.33772680163383484}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2008.4779152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2008.4779152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1865006706","https://openalex.org/W2017983692","https://openalex.org/W2096288172","https://openalex.org/W2105167737","https://openalex.org/W2109395398","https://openalex.org/W2111410899","https://openalex.org/W2112556443","https://openalex.org/W2118880560","https://openalex.org/W2124194540","https://openalex.org/W2129524227","https://openalex.org/W2132532785","https://openalex.org/W2138583748","https://openalex.org/W2140991832","https://openalex.org/W2156447271","https://openalex.org/W2156932943","https://openalex.org/W2543041142","https://openalex.org/W2548730065","https://openalex.org/W6677086388"],"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/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W2292979300","https://openalex.org/W6057950"],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"the":[3,6,9,53,84,88,132,177,197],"authors":[4],"investigate":[5],"use":[7],"of":[8,42,87,176,196],"Wavelet":[10],"Packet":[11],"Decomposition":[12],"(WPD)":[13],"as":[14,58,77,108,141,200],"a":[15,19,120,154,171,188],"preprocessing":[16],"stage":[17],"for":[18,26,94,187],"multiclassifiers":[20],"and":[21,39,45,63,162],"decision":[22,122],"fusion":[23,123],"system":[24],"used":[25,93],"hyperspectral":[27,33,185],"automated":[28],"target":[29],"recognition":[30],"(ATR).":[31],"The":[32,80,174],"signature":[34],"is":[35,66,113,139,147],"transformed":[36],"using":[37,72,182],"WPD,":[38],"each":[40,105,136],"set":[41],"wavelet":[43,81],"detail":[44],"approximation":[46],"coefficients":[47,82],"(terminal":[48],"nodes":[49,86,161],"or":[50],"leaves":[51],"on":[52],"WPD":[54,69],"tree)":[55],"are":[56,91,100,180],"considered":[57],"feature":[59,64,96,110,129,144],"vectors":[60],"Dimensionality":[61],"reduction":[62],"optimization":[65],"performed":[67],"via":[68],"tree":[70,90],"pruning,":[71],"ATR-appropriate":[73],"pruning":[74],"metrics":[75],"such":[76],"class":[78],"separation.":[79],"in":[83,119,153,205],"terminal":[85,106,133,160],"pruned":[89],"then":[92,101],"form":[95],"vectors.":[97],"Three":[98],"methods":[99,179],"investigated:":[102],"(i)":[103],"treating":[104],"node":[107],"independent":[109,117,143,151],"vector":[111,145],"that":[112,146],"input":[114,148],"to":[115,131,149],"an":[116,142,150,183],"classifier":[118,152],"multiclassifier":[121],"(MCDF)":[124],"system,":[125,156],"(ii)":[126],"applying":[127,163],"intelligent":[128],"grouping":[130],"nodes,":[134],"where":[135],"resulting":[137],"group":[138],"treated":[140],"MCDF":[155],"(iii)":[157],"concatenating":[158],"all":[159],"stepwise":[164],"linear":[165],"discriminant":[166],"analysis":[167],"(SLDA)":[168],"along":[169],"with":[170],"single":[172],"classifier.":[173],"efficacy":[175],"proposed":[178],"investigated":[181],"experimental":[184],"database":[186],"remote":[189],"sensing":[190],"agricultural":[191],"application,":[192],"namely":[193],"early":[194],"detection":[195],"disease":[198],"known":[199],"soybean":[201,206],"rust":[202],"(Phakopsora":[203],"pachyrhizi)":[204],"crops.":[207]},"counts_by_year":[{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}