{"id":"https://openalex.org/W4399144504","doi":"https://doi.org/10.1145/3654823.3654908","title":"Hyperspectral Pansharpening Based on Detail Injection and HyperTransformer","display_name":"Hyperspectral Pansharpening Based on Detail Injection and HyperTransformer","publication_year":2024,"publication_date":"2024-03-22","ids":{"openalex":"https://openalex.org/W4399144504","doi":"https://doi.org/10.1145/3654823.3654908"},"language":"en","primary_location":{"id":"doi:10.1145/3654823.3654908","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3654823.3654908","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning","raw_type":"proceedings-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/A5101665071","display_name":"Jiao Jiao","orcid":"https://orcid.org/0000-0003-1747-4635"},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiao Jiao","raw_affiliation_strings":["Space Engineering University, China"],"raw_orcid":"https://orcid.org/0000-0003-1747-4635","affiliations":[{"raw_affiliation_string":"Space Engineering University, China","institution_ids":["https://openalex.org/I4210148107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017731242","display_name":"Chonglei Wang","orcid":"https://orcid.org/0000-0002-0565-552X"},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chonglei Wang","raw_affiliation_strings":["Space Engineering University, China"],"raw_orcid":"https://orcid.org/0000-0002-0565-552X","affiliations":[{"raw_affiliation_string":"Space Engineering University, China","institution_ids":["https://openalex.org/I4210148107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101665071"],"corresponding_institution_ids":["https://openalex.org/I4210148107"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12526806,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"430","last_page":"436"},"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":0.9977999925613403,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9940999746322632,"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/panchromatic-film","display_name":"Panchromatic film","score":0.8876039981842041},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.8096805810928345},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7668820023536682},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7070847749710083},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6733309626579285},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.6358681321144104},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6198520064353943},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6105623245239258},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5119563341140747},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.49751999974250793},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.464573472738266},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45413029193878174},{"id":"https://openalex.org/keywords/fusion-mechanism","display_name":"Fusion mechanism","score":0.428936630487442},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.37558281421661377},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.31908926367759705}],"concepts":[{"id":"https://openalex.org/C107445234","wikidata":"https://www.wikidata.org/wiki/Q280995","display_name":"Panchromatic film","level":3,"score":0.8876039981842041},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.8096805810928345},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7668820023536682},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7070847749710083},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6733309626579285},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.6358681321144104},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6198520064353943},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6105623245239258},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5119563341140747},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.49751999974250793},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.464573472738266},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45413029193878174},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.428936630487442},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.37558281421661377},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.31908926367759705},{"id":"https://openalex.org/C103038307","wikidata":"https://www.wikidata.org/wiki/Q6556360","display_name":"Lipid bilayer fusion","level":3,"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3654823.3654908","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3654823.3654908","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1990231296","https://openalex.org/W2001800591","https://openalex.org/W2021046129","https://openalex.org/W2021384698","https://openalex.org/W2097259623","https://openalex.org/W2103428240","https://openalex.org/W2132984323","https://openalex.org/W2462592242","https://openalex.org/W2803825432","https://openalex.org/W2906771061","https://openalex.org/W2948669395","https://openalex.org/W2963442801","https://openalex.org/W2994765379","https://openalex.org/W3019893222","https://openalex.org/W3102912004","https://openalex.org/W3175432749","https://openalex.org/W3176970595","https://openalex.org/W3181367324","https://openalex.org/W3181737610","https://openalex.org/W4312340363"],"related_works":["https://openalex.org/W4285005667","https://openalex.org/W2950729865","https://openalex.org/W4298392938","https://openalex.org/W2008401355","https://openalex.org/W2385264142","https://openalex.org/W2044102280","https://openalex.org/W2380263558","https://openalex.org/W2992121921","https://openalex.org/W1966079689","https://openalex.org/W1954408549"],"abstract_inverted_index":{"Hyperspectral":[0],"(HS)":[1],"pansharpening":[2,35,64,179],"aims":[3],"to":[4,21,51,80,103,145,154],"fuse":[5,146],"a":[6,13,61],"low":[7,117],"spatial":[8,16,30],"resolution":[9,17,118],"HS":[10,25,63,91,119,159],"image":[11,20,26],"with":[12,27,127],"registered":[14],"high":[15,29],"panchromatic":[18],"(PAN)":[19],"generate":[22],"the":[23,74,82,88,96,105,110,124,135,139,147,151,156,170,173,177],"enhanced":[24],"both":[28,184],"and":[31,46,71,84,90,116,123,150,188],"spectral":[32,85],"resolution.":[33],"Existing":[34],"approaches":[36],"based":[37,66,100],"on":[38,67,101,164],"convolutional":[39],"neural":[40],"networks":[41],"(ConvNets)":[42],"are":[43,132],"poorly":[44],"interpretable":[45],"rarely":[47],"use":[48],"attention":[49,136],"mechanisms":[50],"extract":[52,81],"relevant":[53],"texture":[54,83],"details.":[55],"In":[56],"this":[57],"paper,":[58],"we":[59,94],"present":[60],"novel":[62],"method":[65,175],"detail":[68,106,140,148],"injection":[69,141],"framework":[70,142],"HyperTransformer.":[72],"Firstly,":[73],"feature":[75],"extraction":[76],"sub-network":[77,99],"is":[78,121,143],"used":[79,167],"information":[86,149],"of":[87,172,183],"PAN":[89,115],"images,":[92],"secondly,":[93],"designed":[95],"spatial-spectral":[97],"fusion":[98],"HyperTransformer":[102],"obtain":[104,155],"information,":[107],"in":[108,181],"which":[109],"cross-feature":[111],"space":[112],"dependency":[113],"between":[114],"features":[120,131],"extracted":[122],"high-frequency":[125],"details":[126],"more":[128],"spectrally":[129],"similar":[130],"learned":[133],"by":[134],"mechanism.":[137],"Finally,":[138],"applied":[144],"low-frequency":[152],"component":[153],"final":[157],"high-resolution":[158],"image.":[160],"Comparative":[161],"experiments":[162],"conducted":[163],"three":[165],"widely":[166],"datasets":[168],"demonstrate":[169],"superiority":[171],"proposed":[174],"over":[176],"state-of-the-art":[178],"results":[180],"terms":[182],"subjective":[185],"visual":[186],"effects":[187],"quantitative":[189],"evaluations.":[190]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}