{"id":"https://openalex.org/W4313067217","doi":"https://doi.org/10.1109/igarss46834.2022.9883203","title":"Cross-Frequency Detail Compensation Network for Pansharpening","display_name":"Cross-Frequency Detail Compensation Network for Pansharpening","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4313067217","doi":"https://doi.org/10.1109/igarss46834.2022.9883203"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9883203","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883203","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101667067","display_name":"Xiaonan Zhao","orcid":"https://orcid.org/0000-0003-0738-5858"},"institutions":[{"id":"https://openalex.org/I4210097173","display_name":"Shandong Yingcai University","ror":"https://ror.org/00qhrkk71","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210097173"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao-Nan Zhao","raw_affiliation_strings":["Yingcai Honors College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yingcai Honors College","institution_ids":["https://openalex.org/I4210097173"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100605586","display_name":"Chenyu Zhao","orcid":"https://orcid.org/0009-0000-5681-0596"},"institutions":[{"id":"https://openalex.org/I4210097173","display_name":"Shandong Yingcai University","ror":"https://ror.org/00qhrkk71","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210097173"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen-Yu Zhao","raw_affiliation_strings":["Yingcai Honors College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yingcai Honors College","institution_ids":["https://openalex.org/I4210097173"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061188534","display_name":"Tian-Jing Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210097173","display_name":"Shandong Yingcai University","ror":"https://ror.org/00qhrkk71","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210097173"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian-Jing Zhang","raw_affiliation_strings":["Yingcai Honors College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yingcai Honors College","institution_ids":["https://openalex.org/I4210097173"]}]},{"author_position":"last","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":["School of Mathematical Sciences, University of Electronic Science and Technology of China,Chengdu,China,611731"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, University of Electronic Science and Technology of China,Chengdu,China,611731","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3770","last_page":"3773"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9976999759674072,"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":0.9965000152587891,"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/computer-science","display_name":"Computer science","score":0.8015509843826294},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6486011147499084},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6153029799461365},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.58747398853302},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5588421821594238},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.5303866267204285},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.518886387348175},{"id":"https://openalex.org/keywords/spatial-frequency","display_name":"Spatial frequency","score":0.49840235710144043},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4869312047958374},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.43835124373435974},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4348212480545044},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4244776964187622},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4151468276977539},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.19055688381195068}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8015509843826294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6486011147499084},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6153029799461365},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.58747398853302},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5588421821594238},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.5303866267204285},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.518886387348175},{"id":"https://openalex.org/C100921725","wikidata":"https://www.wikidata.org/wiki/Q1650811","display_name":"Spatial frequency","level":2,"score":0.49840235710144043},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4869312047958374},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.43835124373435974},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4348212480545044},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4244776964187622},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4151468276977539},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.19055688381195068},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss46834.2022.9883203","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883203","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":14,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2462592242","https://openalex.org/W2777033955","https://openalex.org/W2792114281","https://openalex.org/W2962851801","https://openalex.org/W2963007295","https://openalex.org/W2964233199","https://openalex.org/W2988396473","https://openalex.org/W3023991509","https://openalex.org/W3029812440","https://openalex.org/W3096904276","https://openalex.org/W6743087176","https://openalex.org/W6746722832","https://openalex.org/W6785488583"],"related_works":["https://openalex.org/W4318664220","https://openalex.org/W2771047279","https://openalex.org/W4388409104","https://openalex.org/W2124951708","https://openalex.org/W1544811710","https://openalex.org/W172072032","https://openalex.org/W2011962637","https://openalex.org/W2163677711","https://openalex.org/W2036727360","https://openalex.org/W2998538752"],"abstract_inverted_index":{"Pansharpening":[0],"is":[1,86,107],"a":[2,33,67,82,90],"fusion":[3],"technique":[4],"aiming":[5],"at":[6],"improving":[7],"the":[8,53,62,94,100,110,122,128],"spatial":[9,43],"resolution":[10],"of":[11,46,56,130,138],"multispectral":[12],"images":[13],"while":[14,98],"preserving":[15],"spectral":[16],"information.":[17],"Previous":[18],"attempts":[19],"to":[20,25,88,120],"adopt":[21],"CNNs":[22],"have":[23],"led":[24],"significant":[26],"progress":[27],"in":[28,41,61,115,136],"pansharpening,":[29],"but":[30],"always":[31],"with":[32,58],"cumbersome":[34],"network":[35,71],"structure,":[36],"and":[37,44,77,109,141],"there":[38],"exists":[39],"redundancy":[40],"both":[42],"channel":[45],"feature":[47,63],"maps":[48],"learned":[49,111],"by":[50,73],"CNNs.":[51],"Considering":[52],"distinct":[54],"properties":[55],"components":[57],"different":[59,95],"frequencies":[60],"map,":[64],"we":[65],"propose":[66],"cross-frequency":[68,83],"detail":[69,103],"compensation":[70,118],"(CFDCNet)":[72],"processing":[74],"low,":[75],"medium,":[76],"high":[78],"frequency":[79,96],"separately.":[80],"Specifically,":[81],"convolution":[84],"block":[85],"designed":[87],"produce":[89],"representation":[91],"that":[92],"captures":[93],"classes":[97],"achieving":[99],"more":[101],"efficient":[102],"extraction.":[104],"Overall":[105],"pipeline":[106],"progressive,":[108],"features":[112],"are":[113],"fused":[114],"an":[116],"interactive":[117],"manner":[119],"obtain":[121],"final":[123],"output.":[124],"Experimental":[125],"results":[126],"demonstrate":[127],"superiority":[129],"CFDCNet":[131],"over":[132],"state-of-the-art":[133],"pansharpening":[134],"methods":[135],"terms":[137],"visual":[139],"quality":[140],"quantitative":[142],"metrics.":[143]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}