{"id":"https://openalex.org/W2952505275","doi":"https://doi.org/10.1109/igarss.2019.8899098","title":"On Training Deep Networks for Satellite Image Super-Resolution","display_name":"On Training Deep Networks for Satellite Image Super-Resolution","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2952505275","doi":"https://doi.org/10.1109/igarss.2019.8899098","mag":"2952505275"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8899098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1906.06697","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086221093","display_name":"Micha\u0142 Kawulok","orcid":"https://orcid.org/0000-0002-3669-5110"},"institutions":[{"id":"https://openalex.org/I4210151481","display_name":"\u0141ukasiewicz Research Network - Institute of Welding","ror":"https://ror.org/05xx8bb48","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210129336","https://openalex.org/I4210151481"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Michal Kawulok","raw_affiliation_strings":["Future Processing, Gliwice, Poland","Institute of Electrical and Electronics Engineers"],"affiliations":[{"raw_affiliation_string":"Future Processing, Gliwice, Poland","institution_ids":["https://openalex.org/I4210151481"]},{"raw_affiliation_string":"Institute of Electrical and Electronics Engineers","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085915136","display_name":"Szymon Piechaczek","orcid":"https://orcid.org/0000-0003-1249-5314"},"institutions":[{"id":"https://openalex.org/I4210151481","display_name":"\u0141ukasiewicz Research Network - Institute of Welding","ror":"https://ror.org/05xx8bb48","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210129336","https://openalex.org/I4210151481"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Szymon Piechaczek","raw_affiliation_strings":["Future Processing, Gliwice, Poland","Future Processing,,,Gliwice,,Poland"],"affiliations":[{"raw_affiliation_string":"Future Processing, Gliwice, Poland","institution_ids":["https://openalex.org/I4210151481"]},{"raw_affiliation_string":"Future Processing,,,Gliwice,,Poland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016700776","display_name":"Krzysztof Hrynczenko","orcid":"https://orcid.org/0000-0002-7631-0481"},"institutions":[{"id":"https://openalex.org/I4210151481","display_name":"\u0141ukasiewicz Research Network - Institute of Welding","ror":"https://ror.org/05xx8bb48","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210129336","https://openalex.org/I4210151481"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Krzysztof Hrynczenko","raw_affiliation_strings":["Future Processing, Gliwice, Poland","Future Processing,,,Gliwice,,Poland"],"affiliations":[{"raw_affiliation_string":"Future Processing, Gliwice, Poland","institution_ids":["https://openalex.org/I4210151481"]},{"raw_affiliation_string":"Future Processing,,,Gliwice,,Poland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008626424","display_name":"Pawe\u0142 Benecki","orcid":"https://orcid.org/0000-0003-4674-5393"},"institutions":[{"id":"https://openalex.org/I4210151481","display_name":"\u0141ukasiewicz Research Network - Institute of Welding","ror":"https://ror.org/05xx8bb48","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210129336","https://openalex.org/I4210151481"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Pawel Benecki","raw_affiliation_strings":["Future Processing, Gliwice, Poland","Future Processing,,,Gliwice,,Poland"],"affiliations":[{"raw_affiliation_string":"Future Processing, Gliwice, Poland","institution_ids":["https://openalex.org/I4210151481"]},{"raw_affiliation_string":"Future Processing,,,Gliwice,,Poland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057709904","display_name":"Daniel Kostrzewa","orcid":"https://orcid.org/0000-0003-2781-3709"},"institutions":[{"id":"https://openalex.org/I4210151481","display_name":"\u0141ukasiewicz Research Network - Institute of Welding","ror":"https://ror.org/05xx8bb48","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210129336","https://openalex.org/I4210151481"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Daniel Kostrzewa","raw_affiliation_strings":["Future Processing, Gliwice, Poland","Future Processing,,,Gliwice,,Poland"],"affiliations":[{"raw_affiliation_string":"Future Processing, Gliwice, Poland","institution_ids":["https://openalex.org/I4210151481"]},{"raw_affiliation_string":"Future Processing,,,Gliwice,,Poland","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041796575","display_name":"Jakub Nalepa","orcid":"https://orcid.org/0000-0002-4026-1569"},"institutions":[{"id":"https://openalex.org/I4210151481","display_name":"\u0141ukasiewicz Research Network - Institute of Welding","ror":"https://ror.org/05xx8bb48","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210129336","https://openalex.org/I4210151481"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Jakub Nalepa","raw_affiliation_strings":["Future Processing, Gliwice, Poland","Future Processing,,,Gliwice,,Poland"],"affiliations":[{"raw_affiliation_string":"Future Processing, Gliwice, Poland","institution_ids":["https://openalex.org/I4210151481"]},{"raw_affiliation_string":"Future Processing,,,Gliwice,,Poland","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5086221093"],"corresponding_institution_ids":["https://openalex.org/I4210151481"],"apc_list":null,"apc_paid":null,"fwci":0.2044,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.53024315,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3125","last_page":"3128"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9980000257492065,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9907000064849854,"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/bicubic-interpolation","display_name":"Bicubic interpolation","score":0.8611502647399902},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.8583642840385437},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7293277978897095},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6781796216964722},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6475747227668762},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6034463047981262},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.5339556932449341},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5166993141174316},{"id":"https://openalex.org/keywords/superresolution","display_name":"Superresolution","score":0.4834536015987396},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4755924940109253},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.45618075132369995},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4294198155403137},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4266894459724426},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4086032807826996},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3404783606529236},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.27636659145355225},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.17053940892219543},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06234341859817505}],"concepts":[{"id":"https://openalex.org/C49608258","wikidata":"https://www.wikidata.org/wiki/Q611705","display_name":"Bicubic interpolation","level":4,"score":0.8611502647399902},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.8583642840385437},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7293277978897095},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6781796216964722},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6475747227668762},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6034463047981262},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.5339556932449341},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5166993141174316},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.4834536015987396},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4755924940109253},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.45618075132369995},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4294198155403137},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4266894459724426},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4086032807826996},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3404783606529236},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27636659145355225},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.17053940892219543},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06234341859817505},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C171836373","wikidata":"https://www.wikidata.org/wiki/Q2266329","display_name":"Linear interpolation","level":3,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/igarss.2019.8899098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1906.06697","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.06697","pdf_url":"https://arxiv.org/pdf/1906.06697","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2952505275","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1906.06697.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1906.06697","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1906.06697","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1906.06697","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.06697","pdf_url":"https://arxiv.org/pdf/1906.06697","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"},{"score":0.41999998688697815,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2952505275.pdf","grobid_xml":"https://content.openalex.org/works/W2952505275.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W1973788353","https://openalex.org/W2121058967","https://openalex.org/W2122632184","https://openalex.org/W2163935418","https://openalex.org/W2194775991","https://openalex.org/W2242218935","https://openalex.org/W2345557152","https://openalex.org/W2503339013","https://openalex.org/W2884629980","https://openalex.org/W2963470893","https://openalex.org/W6677973867","https://openalex.org/W6683680428","https://openalex.org/W6724673846"],"related_works":["https://openalex.org/W2884629980","https://openalex.org/W2985414621","https://openalex.org/W3017452647","https://openalex.org/W3207766770","https://openalex.org/W3167726866","https://openalex.org/W3207673409","https://openalex.org/W2895769970","https://openalex.org/W3035382243","https://openalex.org/W1973788353","https://openalex.org/W2791901417","https://openalex.org/W2353188469","https://openalex.org/W2900619775","https://openalex.org/W3015280358","https://openalex.org/W3144029257","https://openalex.org/W2565951649","https://openalex.org/W2911583094","https://openalex.org/W2795115631","https://openalex.org/W2968065552","https://openalex.org/W3026601607","https://openalex.org/W3206266434"],"abstract_inverted_index":{"The":[0],"capabilities":[1],"of":[2,20,35,39],"super-resolution":[3],"(SR)":[4],"reconstruction":[5,96],"(i.e.,":[6],"techniques":[7],"for":[8,107,129],"enhancing":[9],"image":[10],"spatial":[11],"resolution)":[12],"have":[13,90],"been":[14,72],"boosted":[15],"recently":[16],"by":[17],"the":[18,53,58,63,86,95,99,104],"use":[19],"deep":[21],"convolutional":[22],"neural":[23],"networks.":[24],"For":[25],"SR,":[26],"they":[27],"are":[28],"learned":[29],"using":[30],"huge":[31],"training":[32,64,87,118],"sets":[33],"composed":[34],"original":[36],"images,":[37],"each":[38],"which":[40],"is":[41,78,102],"coupled":[42],"with":[43,109],"a":[44,91],"low-resolution":[45],"counterpart.":[46],"In":[47],"this":[48,69],"paper,":[49],"we":[50,113],"explore":[51],"how":[52],"SR":[54,127],"performance":[55],"depends":[56],"on":[57,94],"procedure":[59],"employed":[60],"to":[61,67],"obtain":[62],"data.":[65],"Up":[66],"date,":[68],"has":[70],"not":[71,103],"given":[73],"much":[74],"attention-commonly,":[75],"bicubic":[76],"downsampling":[77],"used.":[79],"Our":[80],"extensive":[81],"experimental":[82],"study":[83],"indicates":[84],"that":[85,115],"data":[88,119],"characteristics":[89],"large":[92],"impact":[93],"accuracy,":[97],"and":[98],"widely-adopted":[100],"approach":[101],"most":[105],"effective":[106],"dealing":[108],"satellite":[110],"images.":[111],"Overall,":[112],"argue":[114],"developing":[116],"better":[117],"preparation":[120],"routines":[121],"may":[122],"be":[123],"pivotal":[124],"in":[125],"making":[126],"suitable":[128],"real-world":[130],"applications.":[131]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}