{"id":"https://openalex.org/W4385764295","doi":"https://doi.org/10.24963/ijcai.2023/404","title":"Bidirectional Dilation Transformer for Multispectral and Hyperspectral Image Fusion","display_name":"Bidirectional Dilation Transformer for Multispectral and Hyperspectral Image Fusion","publication_year":2023,"publication_date":"2023-08-01","ids":{"openalex":"https://openalex.org/W4385764295","doi":"https://doi.org/10.24963/ijcai.2023/404"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2023/404","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/404","pdf_url":"https://www.ijcai.org/proceedings/2023/0404.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2023/0404.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088838710","display_name":"Shangqi Deng","orcid":"https://orcid.org/0000-0002-6971-5114"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shangqi Deng","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088224232","display_name":"Liang-Jian Deng","orcid":"https://orcid.org/0000-0003-3178-9772"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang-Jian Deng","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102671142","display_name":"Xiao Wu","orcid":"https://orcid.org/0000-0002-1259-8674"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Wu","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100638440","display_name":"Ran Ran","orcid":"https://orcid.org/0000-0001-9350-1389"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Ran","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020848795","display_name":"Rui Wen","orcid":"https://orcid.org/0000-0002-8522-2053"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Wen","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5088838710"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":4.0229,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.94457007,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3633","last_page":"3641"},"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/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/T11019","display_name":"Image Enhancement Techniques","score":0.9951000213623047,"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/computer-science","display_name":"Computer science","score":0.7565106153488159},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.7347888946533203},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6630278825759888},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6443129777908325},{"id":"https://openalex.org/keywords/dilation","display_name":"Dilation (metric space)","score":0.620689868927002},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5219904184341431},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47259411215782166},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4400457739830017},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4358958899974823},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.42657470703125},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.4228039085865021},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14835545420646667},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.12808829545974731},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08856764435768127},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08356907963752747}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7565106153488159},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.7347888946533203},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6630278825759888},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6443129777908325},{"id":"https://openalex.org/C2780757906","wikidata":"https://www.wikidata.org/wiki/Q5276676","display_name":"Dilation (metric space)","level":2,"score":0.620689868927002},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5219904184341431},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47259411215782166},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4400457739830017},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4358958899974823},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.42657470703125},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.4228039085865021},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14835545420646667},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.12808829545974731},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08856764435768127},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08356907963752747},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2023/404","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/404","pdf_url":"https://www.ijcai.org/proceedings/2023/0404.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2023/404","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/404","pdf_url":"https://www.ijcai.org/proceedings/2023/0404.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1160855140","display_name":null,"funder_award_id":"2022NSFSC0501","funder_id":"https://openalex.org/F4320329861","funder_display_name":"Natural Science Foundation of Sichuan Province"},{"id":"https://openalex.org/G2129173210","display_name":null,"funder_award_id":"12271083","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329861","display_name":"Natural Science Foundation of Sichuan Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385764295.pdf"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1495168473","https://openalex.org/W1977177161","https://openalex.org/W2028513126","https://openalex.org/W2090640831","https://openalex.org/W2168478992","https://openalex.org/W2349229101","https://openalex.org/W2804744787","https://openalex.org/W2910457605","https://openalex.org/W2945202593","https://openalex.org/W2964209782","https://openalex.org/W2964275574","https://openalex.org/W2989355516","https://openalex.org/W3004925702","https://openalex.org/W3009455122","https://openalex.org/W3014967571","https://openalex.org/W3075397214","https://openalex.org/W3083606623","https://openalex.org/W3085879958","https://openalex.org/W3094502228","https://openalex.org/W3138516171","https://openalex.org/W3160949528","https://openalex.org/W3165892790","https://openalex.org/W3207918547","https://openalex.org/W3214821343","https://openalex.org/W4206377169","https://openalex.org/W4225672218","https://openalex.org/W4225982893","https://openalex.org/W4226469049","https://openalex.org/W4285119709","https://openalex.org/W4287122968","https://openalex.org/W4287274255","https://openalex.org/W4288064619","https://openalex.org/W4306815570","https://openalex.org/W4309845474","https://openalex.org/W4312331860","https://openalex.org/W4313071068","https://openalex.org/W4319663728"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W4318664220","https://openalex.org/W2022304901","https://openalex.org/W2018850895","https://openalex.org/W1987483041","https://openalex.org/W2988577871","https://openalex.org/W4391030644","https://openalex.org/W4205174160"],"abstract_inverted_index":{"Transformer-based":[0],"methods":[1],"have":[2],"proven":[3],"to":[4,70,107,120,165],"be":[5,216],"effective":[6],"in":[7,22,184,188],"achieving":[8],"long-distance":[9],"modeling,":[10],"capturing":[11],"the":[12,28,53,62,77,109,115,130,137,147,156,168,185,203,212,219,223],"spatial":[13,39,55,138,176],"and":[14,17,42,100,114,146,159,200,209],"spectral":[15,43],"information,":[16],"exhibiting":[18],"strong":[19],"inductive":[20],"bias":[21],"various":[23],"computer":[24],"vision":[25,86],"tasks.":[26,87,122],"Generally,":[27],"Transformer":[29,96],"model":[30],"includes":[31],"two":[32,127,195],"common":[33],"modes":[34],"of":[35,111,126,205,222],"multi-head":[36],"self-attention":[37,69],"(MSA):":[38],"MSA":[40,44,113],"(Spa-MSA)":[41],"(Spe-MSA).":[45],"However,":[46],"Spa-MSA":[47,132],"is":[48,82],"computationally":[49],"efficient":[50],"but":[51,74],"limits":[52],"global":[54],"response":[56],"within":[57,155],"a":[58,93,142,180],"local":[59,79,161],"window.":[60],"On":[61],"other":[63],"hand,":[64],"Spe-MSA":[65,149],"can":[66],"calculate":[67],"channel":[68],"accommodate":[71],"high-resolution":[72],"images,":[73],"it":[75],"disregards":[76],"crucial":[78],"information":[80,118,170],"that":[81],"essential":[83],"for":[84,98],"low-level":[85],"In":[88],"this":[89],"study,":[90],"we":[91,178],"propose":[92],"bidirectional":[94,181],"dilation":[95,131],"(BDT)":[97],"multispectral":[99],"hyperspectral":[101],"image":[102],"fusion":[103],"(MHIF),":[104],"which":[105,134,151],"aims":[106],"leverage":[108],"advantages":[110],"both":[112,172,207],"latent":[116,153],"multiscale":[117,169],"specific":[119],"MHIF":[121],"The":[123],"BDT":[124,206],"consists":[125],"designed":[128],"modules:":[129],"(D-Spa),":[133],"dynamically":[135],"expands":[136],"receptive":[139],"field":[140],"through":[141],"given":[143],"hollow":[144],"strategy,":[145],"grouped":[148],"(G-Spe),":[150],"extracts":[152],"features":[154],"feature":[157],"map":[158],"learns":[160],"data":[162],"behavior.":[163],"Additionally,":[164],"fully":[166],"exploit":[167],"from":[171],"inputs":[173],"with":[174],"different":[175],"resolutions,":[177],"employ":[179],"hierarchy":[182],"strategy":[183],"BDT,":[186],"resulting":[187],"improved":[189],"performance.":[190],"Finally,":[191],"extensive":[192],"experiments":[193],"on":[194],"commonly":[196],"used":[197],"datasets,":[198],"CAVE":[199],"Harvard,":[201],"demonstrate":[202],"superiority":[204],"visually":[208],"quantitatively.":[210],"Furthermore,":[211],"related":[213],"code":[214],"will":[215],"available":[217],"at":[218],"GitHub":[220],"page":[221],"authors.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":2}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}