{"id":"https://openalex.org/W4391947493","doi":"https://doi.org/10.1186/s13634-024-01118-2","title":"Image fusion research based on the Haar-like multi-scale analysis","display_name":"Image fusion research based on the Haar-like multi-scale analysis","publication_year":2024,"publication_date":"2024-02-19","ids":{"openalex":"https://openalex.org/W4391947493","doi":"https://doi.org/10.1186/s13634-024-01118-2"},"language":"en","primary_location":{"id":"doi:10.1186/s13634-024-01118-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-024-01118-2","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-024-01118-2","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1110-8657","issn":["1110-8657","1687-0433","1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-024-01118-2","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101934445","display_name":"Xiaoliang Zhu","orcid":"https://orcid.org/0000-0002-4238-1396"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoliang Zhu","raw_affiliation_strings":["College of Software, Xinjiang University, \u00dcr\u00fcmqi, 830008, China","Xinjiang Uygur Autonomous Region Big Data and Intelligent Software Xinjiang Uygur Autonomous Region Engineering Research Center, Xinjiang University, \u00dcr\u00fcmqi, 830008, China"],"raw_orcid":"https://orcid.org/0000-0002-4238-1396","affiliations":[{"raw_affiliation_string":"College of Software, Xinjiang University, \u00dcr\u00fcmqi, 830008, China","institution_ids":["https://openalex.org/I96908189"]},{"raw_affiliation_string":"Xinjiang Uygur Autonomous Region Big Data and Intelligent Software Xinjiang Uygur Autonomous Region Engineering Research Center, Xinjiang University, \u00dcr\u00fcmqi, 830008, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109754271","display_name":"Mengke Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I154093214","display_name":"Xinjiang Medical University","ror":"https://ror.org/01p455v08","country_code":"CN","type":"education","lineage":["https://openalex.org/I154093214"]},{"id":"https://openalex.org/I4210102015","display_name":"Tumor Hospital of Xinjiang Medical University","ror":"https://ror.org/015tqbb95","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210102015"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengke Wen","raw_affiliation_strings":["Affiliated Tumor Hospital, Xinjiang Medical University, \u00dcr\u00fcmqi, 830011, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Affiliated Tumor Hospital, Xinjiang Medical University, \u00dcr\u00fcmqi, 830011, China","institution_ids":["https://openalex.org/I154093214","https://openalex.org/I4210102015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101934445"],"corresponding_institution_ids":["https://openalex.org/I96908189"],"apc_list":{"value":1790,"currency":"USD","value_usd":1790},"apc_paid":{"value":1790,"currency":"USD","value_usd":1790},"fwci":0.6895,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.68355788,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"2024","issue":"1","first_page":null,"last_page":null},"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":0.9972000122070312,"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":0.9965999722480774,"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/image-fusion","display_name":"Image fusion","score":0.7796704769134521},{"id":"https://openalex.org/keywords/haar","display_name":"Haar","score":0.6872467994689941},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6719960570335388},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.6478582620620728},{"id":"https://openalex.org/keywords/haar-wavelet","display_name":"Haar wavelet","score":0.6477640271186829},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6360774040222168},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6121663451194763},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5755479335784912},{"id":"https://openalex.org/keywords/fusion-rules","display_name":"Fusion rules","score":0.5313858389854431},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5272668600082397},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4809674322605133},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.46328940987586975},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.43817728757858276},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.42451682686805725},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.41024166345596313},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.32330939173698425},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27770859003067017},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10176783800125122}],"concepts":[{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.7796704769134521},{"id":"https://openalex.org/C187029792","wikidata":"https://www.wikidata.org/wiki/Q2179112","display_name":"Haar","level":3,"score":0.6872467994689941},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6719960570335388},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.6478582620620728},{"id":"https://openalex.org/C2780423554","wikidata":"https://www.wikidata.org/wiki/Q766198","display_name":"Haar wavelet","level":5,"score":0.6477640271186829},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6360774040222168},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6121663451194763},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5755479335784912},{"id":"https://openalex.org/C2778971668","wikidata":"https://www.wikidata.org/wiki/Q5510284","display_name":"Fusion rules","level":4,"score":0.5313858389854431},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5272668600082397},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4809674322605133},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.46328940987586975},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.43817728757858276},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.42451682686805725},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.41024166345596313},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.32330939173698425},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27770859003067017},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10176783800125122},{"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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s13634-024-01118-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-024-01118-2","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-024-01118-2","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1110-8657","issn":["1110-8657","1687-0433","1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:63b883d8417549c9b0ef4666c220f925","is_oa":true,"landing_page_url":"https://doaj.org/article/63b883d8417549c9b0ef4666c220f925","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-17 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s13634-024-01118-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-024-01118-2","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-024-01118-2","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1110-8657","issn":["1110-8657","1687-0433","1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3507899275","display_name":null,"funder_award_id":"XJDX2022YALK11","funder_id":"https://openalex.org/F4320325419","funder_display_name":"Xinjiang University"},{"id":"https://openalex.org/G5906681709","display_name":null,"funder_award_id":"2022D01C425","funder_id":"https://openalex.org/F4320311028","funder_display_name":"Natural Science Foundation of Xinjiang Province"}],"funders":[{"id":"https://openalex.org/F4320311028","display_name":"Natural Science Foundation of Xinjiang Province","ror":null},{"id":"https://openalex.org/F4320325419","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13"},{"id":"https://openalex.org/F4320328898","display_name":"Natural Science Foundation of Xinjiang","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391947493.pdf","grobid_xml":"https://content.openalex.org/works/W4391947493.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1991892016","https://openalex.org/W2004997234","https://openalex.org/W2014886478","https://openalex.org/W2056346283","https://openalex.org/W2094824638","https://openalex.org/W2133665775","https://openalex.org/W2289413700","https://openalex.org/W2586807479","https://openalex.org/W2732331263","https://openalex.org/W2782223379","https://openalex.org/W2907490238","https://openalex.org/W2912551047","https://openalex.org/W2947338419","https://openalex.org/W3016322158","https://openalex.org/W3043627836","https://openalex.org/W3096242307","https://openalex.org/W3111354027","https://openalex.org/W3122103149","https://openalex.org/W3126442124","https://openalex.org/W3126994406","https://openalex.org/W3182264287","https://openalex.org/W3184721878","https://openalex.org/W3200043585","https://openalex.org/W3204568695","https://openalex.org/W3216123027","https://openalex.org/W4206306933","https://openalex.org/W4224262076","https://openalex.org/W4293339422","https://openalex.org/W4306954497"],"related_works":["https://openalex.org/W4361795924","https://openalex.org/W984746159","https://openalex.org/W2766849256","https://openalex.org/W1523827626","https://openalex.org/W1999916501","https://openalex.org/W4232769230","https://openalex.org/W2005569824","https://openalex.org/W4239324723","https://openalex.org/W2892809389","https://openalex.org/W1749665274"],"abstract_inverted_index":{"Abstract":[0],"In":[1],"view":[2],"of":[3,13,62,137,155],"the":[4,11,14,36,47,63,66,82,89,93,98,102,134,138,163,168,171,175,179,196],"serious":[5],"color":[6,180,185],"and":[7,33,57,77,92,101,123,151,178,192],"definition":[8,177],"distortion":[9],"in":[10,26,88,105,167,174,184],"process":[12],"traditional":[15],"image":[16,38],"fusion,":[17],"this":[18],"study":[19,121,169],"proposes":[20],"a":[21,130],"Haar-like":[22],"multi-scale":[23],"analysis":[24],"model,":[25],"which":[27],"Haar":[28,49],"wavelet":[29,50],"has":[30],"been":[31],"modified":[32],"used":[34,142],"for":[35,143],"medical":[37,139],"fusion":[39,84,131,157,164],"to":[40,96,115,128],"obtain":[41,170],"even":[42],"better":[43],"results.":[44],"Firstly,":[45],"when":[46],"improved":[48],"basis":[51],"function":[52],"is":[53,68],"translated,":[54],"inner":[55],"product":[56],"down-sampled":[58],"with":[59,153,195],"each":[60,106,117],"band":[61,67],"original":[64],"image,":[65],"decomposed":[69],"into":[70],"four":[71,109],"sub-images":[72,104],"containing":[73],"one":[74],"low-frequency":[75,90,99],"subdomain":[76],"three":[78],"high-frequency":[79,94,103],"subdomains.":[80],"Secondly,":[81],"different":[83],"rules":[85],"are":[86,113,141,149],"applied":[87],"domain":[91],"domains":[95,112],"get":[97],"sub-image":[100],"band.":[107,119],"The":[108,120,146],"new":[110,118,126],"sub-frequency":[111],"inverse-decomposed":[114],"reconstruct":[116],"configures":[122],"synthesizes":[124],"these":[125],"bands":[127],"produce":[129],"image.":[132],"Lastly,":[133],"two":[135],"groups":[136],"images":[140],"experimental":[144],"simulation.":[145],"Experimental":[147],"results":[148],"analyzed":[150],"compared":[152],"those":[154],"other":[156,197],"methods.":[158,198],"It":[159],"can":[160],"be":[161],"found":[162],"method":[165],"proposed":[166],"superior":[172],"effects":[173],"spatial":[176],"depth":[181],"feature,":[182],"especially":[183],"criteria":[186],"such":[187],"as":[188],"OP,":[189],"SpD,":[190],"CR":[191],"SSIM,":[193],"comparing":[194]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}