{"id":"https://openalex.org/W2901400766","doi":"https://doi.org/10.1109/igarss.2018.8517817","title":"A Multi-Direction Subbands and Deep Neural Networks Bassed Pan-Sharpening Method","display_name":"A Multi-Direction Subbands and Deep Neural Networks Bassed Pan-Sharpening Method","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2901400766","doi":"https://doi.org/10.1109/igarss.2018.8517817","mag":"2901400766"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8517817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","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/A5006226649","display_name":"Wei Huang","orcid":"https://orcid.org/0000-0002-0095-1354"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Huang","raw_affiliation_strings":["School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, P. R. China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101563213","display_name":"Xuan Fei","orcid":"https://orcid.org/0000-0002-6637-9469"},"institutions":[{"id":"https://openalex.org/I36152291","display_name":"Henan University of Technology","ror":"https://ror.org/05sbgwt55","country_code":"CN","type":"education","lineage":["https://openalex.org/I36152291"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Fei","raw_affiliation_strings":["College of Information Science and Engineering, Henan University of Technology, Zhengzhou, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Henan University of Technology, Zhengzhou, P. R. China","institution_ids":["https://openalex.org/I36152291"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061114386","display_name":"Junru Yin","orcid":"https://orcid.org/0000-0002-7101-1140"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junru Yin","raw_affiliation_strings":["School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, P. R. China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100351175","display_name":"Yan Liu","orcid":"https://orcid.org/0000-0003-4242-4840"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Liu","raw_affiliation_strings":["School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, P. R. China","institution_ids":["https://openalex.org/I23171815"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.19019452,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"5139","last_page":"5142"},"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":0.9993000030517578,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9973000288009644,"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/contourlet","display_name":"Contourlet","score":0.9071837663650513},{"id":"https://openalex.org/keywords/sharpening","display_name":"Sharpening","score":0.845505952835083},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7022170424461365},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6070038080215454},{"id":"https://openalex.org/keywords/panchromatic-film","display_name":"Panchromatic film","score":0.6044347286224365},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.561333179473877},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.5609353184700012},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.5454015731811523},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48273155093193054},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4591924250125885},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4535773694515228},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4413113594055176},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.440066933631897},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.4114302396774292},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.17681661248207092},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1259363293647766},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.11879140138626099}],"concepts":[{"id":"https://openalex.org/C20479862","wikidata":"https://www.wikidata.org/wiki/Q5165589","display_name":"Contourlet","level":4,"score":0.9071837663650513},{"id":"https://openalex.org/C2781137444","wikidata":"https://www.wikidata.org/wiki/Q237105","display_name":"Sharpening","level":2,"score":0.845505952835083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7022170424461365},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6070038080215454},{"id":"https://openalex.org/C107445234","wikidata":"https://www.wikidata.org/wiki/Q280995","display_name":"Panchromatic film","level":3,"score":0.6044347286224365},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.561333179473877},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.5609353184700012},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.5454015731811523},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48273155093193054},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4591924250125885},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4535773694515228},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4413113594055176},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.440066933631897},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.4114302396774292},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.17681661248207092},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1259363293647766},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.11879140138626099},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8517817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W54434497","https://openalex.org/W1885185971","https://openalex.org/W2106002835","https://openalex.org/W2111924917","https://openalex.org/W2129953395","https://openalex.org/W2144436897","https://openalex.org/W2154789478","https://openalex.org/W2737219040"],"related_works":["https://openalex.org/W4254327447","https://openalex.org/W2816335205","https://openalex.org/W2158371478","https://openalex.org/W2033186943","https://openalex.org/W2158027388","https://openalex.org/W2182807969","https://openalex.org/W2084382156","https://openalex.org/W2733652285","https://openalex.org/W2019692878","https://openalex.org/W4313315820"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,160],"pan-sharpening":[4],"method":[5,50,211],"based":[6],"on":[7,117,200],"multi-direction":[8,20],"subbands":[9,37,45,84,105,131,154],"and":[10,19,41,62,173,196,222],"deep":[11,92],"neural":[12,93],"networks.":[13],"First,":[14],"by":[15,141,166,189],"utilizing":[16],"the":[17,23,34,42,54,63,78,81,91,99,111,118,145,151,168,174,191,201,209],"multi-scale":[18],"properties":[21],"of":[22,59,68,80,88,102,106,121,132,144,155,179,194,218],"nonsubsampled":[24],"contourlet":[25],"transform":[26,193],"(NSCT),":[27],"panchromatic":[28],"(PAN)":[29],"image":[30,61,100,138,186],"is":[31,96,139,150,164,187],"decomposed":[32],"into":[33],"low":[35,64,123,176],"frequency":[36,44,56,65,83,104,130,153,171,177],"in":[38,46,73,85,110,216],"different":[39,47,86],"resolutions":[40],"high":[43,55,82,103,129,134,152,170],"directions.":[48],"Pan-sharpening":[49],"aims":[51],"to":[52,75],"fuse":[53],"subband":[57,66,162,172,178,203],"coefficients":[58,67],"PAN":[60,89,107],"multispectral":[69],"(MS)":[70],"image.":[71,108,127,158,182],"Second,":[72],"order":[74],"better":[76],"extract":[77],"feature":[79],"directions":[87],"image,":[90],"network":[94],"(DNN)":[95],"trained":[97,146],"using":[98],"patches":[101],"Third,":[109],"fusion":[112],"stage,":[113],"we":[114],"exploit":[115],"NSCT":[116,195],"principal":[119],"component":[120],"resampled":[122],"resolution":[124,135],"(LR)":[125],"MS":[126,137,157,181,185],"The":[128,183,205],"output":[133],"(HR)":[136],"obtained":[140,165],"forward":[142],"propagation":[143],"DNN,":[147],"which":[148],"input":[149],"LR":[156,180],"Finally,":[159],"new":[161,202],"set":[163],"fusing":[167],"reconstructed":[169],"original":[175],"HR":[184],"produced":[188],"executing":[190],"inverse":[192],"adaptive":[197],"PCA":[198],"(A-PCA)":[199],"set.":[204],"experimental":[206],"results":[207],"show":[208],"proposed":[210],"outperforms":[212],"other":[213],"well-known":[214],"methods":[215],"terms":[217],"both":[219],"objective":[220],"measurements":[221],"visual":[223],"evaluation.":[224]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
