{"id":"https://openalex.org/W1789258705","doi":"https://doi.org/10.1117/1.3099703","title":"Region-based image fusion method using bidimensional empirical mode decomposition","display_name":"Region-based image fusion method using bidimensional empirical mode decomposition","publication_year":2009,"publication_date":"2009-01-01","ids":{"openalex":"https://openalex.org/W1789258705","doi":"https://doi.org/10.1117/1.3099703","mag":"1789258705"},"language":"en","primary_location":{"id":"doi:10.1117/1.3099703","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.3099703","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/A5101678402","display_name":"Zheng Qin","orcid":"https://orcid.org/0000-0002-4637-2518"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zheng Qin","raw_affiliation_strings":["Tsinghua Univ. (China)","#N##TAB##TAB##TAB##TAB# Tsinghua University, China#N##TAB##TAB##TAB#"],"affiliations":[{"raw_affiliation_string":"Tsinghua Univ. (China)","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"#N##TAB##TAB##TAB##TAB# Tsinghua University, China#N##TAB##TAB##TAB#","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101678402"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":3.162,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.91465994,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"18","issue":"1","first_page":"013008","last_page":"013008"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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":0.9962000250816345,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9873999953269958,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.8940820693969727},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.8134801387786865},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6158446073532104},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5627111196517944},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5501233339309692},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.539253830909729},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5004076957702637},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4497886300086975},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4357941150665283},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.43324393033981323},{"id":"https://openalex.org/keywords/composite-image-filter","display_name":"Composite image filter","score":0.41336894035339355},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4058780372142792},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39946889877319336},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2703453302383423}],"concepts":[{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.8940820693969727},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.8134801387786865},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6158446073532104},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5627111196517944},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5501233339309692},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.539253830909729},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5004076957702637},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4497886300086975},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4357941150665283},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.43324393033981323},{"id":"https://openalex.org/C78087231","wikidata":"https://www.wikidata.org/wiki/Q5156759","display_name":"Composite image filter","level":3,"score":0.41336894035339355},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4058780372142792},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39946889877319336},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2703453302383423},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/1.3099703","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.3099703","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1763453483","https://openalex.org/W1773037563","https://openalex.org/W1976836781","https://openalex.org/W1986629820","https://openalex.org/W1999478155","https://openalex.org/W2005682787","https://openalex.org/W2007221293","https://openalex.org/W2026651590","https://openalex.org/W2028555274","https://openalex.org/W2048661006","https://openalex.org/W2049573171","https://openalex.org/W2050002311","https://openalex.org/W2056346283","https://openalex.org/W2056651867","https://openalex.org/W2061295289","https://openalex.org/W2077896037","https://openalex.org/W2089809277","https://openalex.org/W2091484864","https://openalex.org/W2105505196","https://openalex.org/W2119388146","https://openalex.org/W2123325761","https://openalex.org/W2131168375","https://openalex.org/W2132746638","https://openalex.org/W2150072852","https://openalex.org/W2157840858","https://openalex.org/W2170163526","https://openalex.org/W2172070753"],"related_works":["https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W2116037602","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2549658594","https://openalex.org/W2095903272","https://openalex.org/W2370195708","https://openalex.org/W1490651872","https://openalex.org/W2139242969"],"abstract_inverted_index":{"Youzhi":[0],"Zheng":[1,13],"Tsinghua":[2,15],"University,":[3,16],"Department":[4],"of":[5,18,74,96,135],"Computer":[6],"Science":[7],"and":[8,105,139],"Technology,":[9],"Beijing,":[10,20],"China":[11,21],"100084":[12,22],"Qin":[14],"School":[17],"Software,":[19],"We":[23],"propose":[24],"a":[25,46,72,82],"novel":[26],"multiscale":[27],"decomposition":[28,42,49,55],"(MSD)":[29],"image":[30,36,123],"fusion":[31,37,86,124,131],"algorithm,":[32],"which":[33,57],"is":[34,45,87,111],"region-based":[35],"using":[38],"bidimensional":[39],"empirical":[40,53],"mode":[41,54,76],"(BEMD).":[43],"BEMD":[44,103,109],"2-D":[47],"data-driven":[48],"derived":[50],"from":[51],"the":[52,94,97,107,115,121],"(EMD),":[56],"does":[58],"not":[59],"require":[60],"predetermined":[61],"filter":[62],"or":[63],"wavelet":[64],"function.":[65],"The":[66,85],"input":[67,98],"images":[68,99],"are":[69],"decomposed":[70],"into":[71],"number":[73],"intrinsic":[75],"functions":[77],"(IMFs)":[78],"as":[79,81],"well":[80],"residual":[83],"image.":[84,117],"performed":[88],"region":[89,91],"by":[90],"based":[92],"on":[93],"segmentations":[95],"to":[100,113],"produce":[101],"composite":[102],"representation,":[104],"then":[106],"inverse":[108],"transform":[110],"applied":[112],"obtain":[114],"fused":[116],"Experiments":[118],"show":[119],"that":[120],"proposed":[122],"algorithm":[125],"provides":[126],"superior":[127],"performance":[128],"over":[129],"traditional":[130],"schemes":[132],"in":[133],"terms":[134],"both":[136],"objective":[137],"metrics":[138],"visual":[140],"quality.":[141]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}