{"id":"https://openalex.org/W2050470336","doi":"https://doi.org/10.1117/1.2952851","title":"Wavelet packet transform basis selection method for set partitioning in hierarchical trees","display_name":"Wavelet packet transform basis selection method for set partitioning in hierarchical trees","publication_year":2008,"publication_date":"2008-07-01","ids":{"openalex":"https://openalex.org/W2050470336","doi":"https://doi.org/10.1117/1.2952851","mag":"2050470336"},"language":"en","primary_location":{"id":"doi:10.1117/1.2952851","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.2952851","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electronic Imaging","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/A5044469907","display_name":"Ashraf A. Kassim","orcid":"https://orcid.org/0000-0001-7435-8564"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Ashraf A. Kassim","raw_affiliation_strings":["Nat. Univ. of Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nat. Univ. of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5044469907"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":0.7011,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.72790981,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"17","issue":"3","first_page":"033007","last_page":"033007"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9984999895095825,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9911999702453613,"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/set-partitioning-in-hierarchical-trees","display_name":"Set partitioning in hierarchical trees","score":0.9530417323112488},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.7212256193161011},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.7083837985992432},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.670075535774231},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5809392929077148},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5736767649650574},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5167161822319031},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5059635043144226},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.41995781660079956},{"id":"https://openalex.org/keywords/tree-structure","display_name":"Tree structure","score":0.4194296598434448},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.41196194291114807},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39518821239471436},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3315478265285492},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.3273005485534668},{"id":"https://openalex.org/keywords/binary-tree","display_name":"Binary tree","score":0.11158022284507751},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08757641911506653}],"concepts":[{"id":"https://openalex.org/C136968285","wikidata":"https://www.wikidata.org/wiki/Q3246374","display_name":"Set partitioning in hierarchical trees","level":5,"score":0.9530417323112488},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.7212256193161011},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.7083837985992432},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.670075535774231},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5809392929077148},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5736767649650574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5167161822319031},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5059635043144226},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.41995781660079956},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.4194296598434448},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.41196194291114807},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39518821239471436},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3315478265285492},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.3273005485534668},{"id":"https://openalex.org/C197855036","wikidata":"https://www.wikidata.org/wiki/Q380172","display_name":"Binary tree","level":2,"score":0.11158022284507751},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08757641911506653},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1117/1.2952851","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.2952851","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electronic Imaging","raw_type":"journal-article"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/57800","is_oa":false,"landing_page_url":"http://scholarbank.nus.edu.sg/handle/10635/57800","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8700000047683716}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1587492102","https://openalex.org/W1604810369","https://openalex.org/W1902139662","https://openalex.org/W1997867715","https://openalex.org/W2034805081","https://openalex.org/W2097643379","https://openalex.org/W2115533181","https://openalex.org/W2130561641","https://openalex.org/W2138334626","https://openalex.org/W2139860413","https://openalex.org/W2142276208","https://openalex.org/W2149695488","https://openalex.org/W2156447271","https://openalex.org/W2158987337"],"related_works":["https://openalex.org/W2588415845","https://openalex.org/W2380372197","https://openalex.org/W2131447689","https://openalex.org/W68308810","https://openalex.org/W2053682625","https://openalex.org/W1986475093","https://openalex.org/W2085792030","https://openalex.org/W1588899229","https://openalex.org/W1967182499","https://openalex.org/W2205192157"],"abstract_inverted_index":{"The":[0,92],"dyadic":[1],"wavelet-based":[2],"set":[3],"partitioning":[4],"in":[5,12],"hierarchical":[6],"trees":[7,85],"(SPIHT)":[8],"is":[9,22,44,109],"highly":[10,102],"efficient":[11],"coding":[13,98,118],"nontextured":[14],"images":[15],"while":[16],"the":[17,34,40,57,61,78,106,112],"wavelet":[18],"packet":[19],"transform":[20],"(WPT)":[21],"able":[23],"to":[24,38,60],"provide":[25],"an":[26,69],"optimal":[27,70],"representation":[28],"for":[29,67,73,101],"textured":[30,103],"images.":[31,104],"However,":[32],"incorporating":[33],"WPT":[35,71,108],"with":[36,111],"SPIHT":[37,43,117],"improve":[39],"performance":[41],"of":[42],"not":[45],"as":[46,48,83,86],"straightforward":[47],"it":[49],"would":[50],"seem.":[51],"Although":[52],"previous":[53],"solutions":[54],"generally":[55],"adapt":[56],"zero-tree":[58],"structure":[59],"WPT,":[62],"we":[63],"introduce":[64],"a":[65],"method":[66],"selecting":[68],"basis":[72],"SPIHT,":[74],"which":[75],"efficiently":[76],"compacts":[77],"high-frequency":[79],"subband":[80],"energy":[81],"into":[82],"few":[84],"possible":[87],"and":[88,114],"avoids":[89],"parental":[90],"conflicts.":[91],"proposed":[93],"SPIHT-WPT":[94],"coder":[95],"achieves":[96],"improved":[97],"gains,":[99],"especially":[100],"Furthermore,":[105],"selected":[107],"compatible":[110],"region-of-interest":[113],"error":[115],"resilient":[116],"schemes.":[119]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}