{"id":"https://openalex.org/W3204316335","doi":"https://doi.org/10.1109/inista52262.2021.9548453","title":"Efficient Resolution Enhancement of JPEG2000 Compressed Multispectral Images Using Deep Super-resolution Methods","display_name":"Efficient Resolution Enhancement of JPEG2000 Compressed Multispectral Images Using Deep Super-resolution Methods","publication_year":2021,"publication_date":"2021-08-25","ids":{"openalex":"https://openalex.org/W3204316335","doi":"https://doi.org/10.1109/inista52262.2021.9548453","mag":"3204316335"},"language":"en","primary_location":{"id":"doi:10.1109/inista52262.2021.9548453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/inista52262.2021.9548453","pdf_url":null,"source":{"id":"https://openalex.org/S4306498847","display_name":"2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","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":"2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","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/A5007879522","display_name":"Ali Can Karaca","orcid":"https://orcid.org/0000-0002-6835-7634"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ali Can Karaca","raw_affiliation_strings":["Y\u0131ld\u0131z Technical University, \u0130stanbul, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Y\u0131ld\u0131z Technical University, \u0130stanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054316597","display_name":"\u0130brahim U\u00e7urmak","orcid":null},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ibrahim Ucurmak","raw_affiliation_strings":["Y\u0131ld\u0131z Technical University, \u0130stanbul, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Y\u0131ld\u0131z Technical University, \u0130stanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090504203","display_name":"M. Kemal G\u00fcll\u00fc","orcid":"https://orcid.org/0000-0003-2310-2985"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Mehmet Kemal Gullu","raw_affiliation_strings":["Y\u0131ld\u0131z Technical University, \u0130stanbul, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Y\u0131ld\u0131z Technical University, \u0130stanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4101805"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12513574,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9998000264167786,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.9325469732284546},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.7610992193222046},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6780992746353149},{"id":"https://openalex.org/keywords/jpeg-2000","display_name":"JPEG 2000","score":0.6426644325256348},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.6294065117835999},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5985724925994873},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5653052926063538},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5531359314918518},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.549359917640686},{"id":"https://openalex.org/keywords/bicubic-interpolation","display_name":"Bicubic interpolation","score":0.49941539764404297},{"id":"https://openalex.org/keywords/multispectral-pattern-recognition","display_name":"Multispectral pattern recognition","score":0.45420971512794495},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4197624623775482},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.31992238759994507},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.31971269845962524},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2741463780403137},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15062016248703003},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1499612033367157}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.9325469732284546},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.7610992193222046},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6780992746353149},{"id":"https://openalex.org/C69216139","wikidata":"https://www.wikidata.org/wiki/Q931783","display_name":"JPEG 2000","level":5,"score":0.6426644325256348},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.6294065117835999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5985724925994873},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5653052926063538},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5531359314918518},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.549359917640686},{"id":"https://openalex.org/C49608258","wikidata":"https://www.wikidata.org/wiki/Q611705","display_name":"Bicubic interpolation","level":4,"score":0.49941539764404297},{"id":"https://openalex.org/C104541649","wikidata":"https://www.wikidata.org/wiki/Q6935090","display_name":"Multispectral pattern recognition","level":3,"score":0.45420971512794495},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4197624623775482},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.31992238759994507},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.31971269845962524},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2741463780403137},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15062016248703003},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1499612033367157},{"id":"https://openalex.org/C171836373","wikidata":"https://www.wikidata.org/wiki/Q2266329","display_name":"Linear interpolation","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/inista52262.2021.9548453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/inista52262.2021.9548453","pdf_url":null,"source":{"id":"https://openalex.org/S4306498847","display_name":"2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","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":"2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","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":22,"referenced_works":["https://openalex.org/W2158548804","https://openalex.org/W2242218935","https://openalex.org/W2783978965","https://openalex.org/W2807355972","https://openalex.org/W2887695188","https://openalex.org/W2888285221","https://openalex.org/W2896365540","https://openalex.org/W2937843000","https://openalex.org/W2945139922","https://openalex.org/W2954232984","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2969321876","https://openalex.org/W2988111912","https://openalex.org/W3014422499","https://openalex.org/W3035629584","https://openalex.org/W3042093094","https://openalex.org/W3102189958","https://openalex.org/W3119157339","https://openalex.org/W3124561108","https://openalex.org/W6754089586","https://openalex.org/W6788168317"],"related_works":["https://openalex.org/W3202223591","https://openalex.org/W3216158842","https://openalex.org/W4288103895","https://openalex.org/W3012322483","https://openalex.org/W3203374800","https://openalex.org/W2974792966","https://openalex.org/W2914107945","https://openalex.org/W2801811999","https://openalex.org/W4293519389","https://openalex.org/W4291801625"],"abstract_inverted_index":{"Multispectral":[0],"imaging":[1,18],"is":[2,96,111],"one":[3],"of":[4,32,74,88,100,147],"the":[5,33,42,72,85,93,108,122,126,134,168],"most":[6],"important":[7],"Earth":[8],"observation":[9],"techniques":[10],"in":[11,24,57,145],"remote":[12,58],"sensing.":[13],"Although":[14],"their":[15],"advantages,":[16],"multispectral":[17,34,94],"systems":[19],"continuously":[20],"capture":[21],"images":[22,43],"resulting":[23,109],"enormous":[25],"data":[26],"volumes.":[27],"To":[28],"this":[29,68],"end,":[30],"some":[31],"satellites":[35],"use":[36],"JPEG2000":[37,89],"based":[38],"compression":[39,51,127],"methods.":[40],"However,":[41],"that":[44,167],"are":[45,118,143],"compressed":[46,90,112],"at":[47,98],"low":[48],"bit-rates":[49],"contain":[50],"artifacts":[52],"and":[53,65,82,106,124,160,175],"may":[54],"present":[55],"low-performances":[56],"sensing":[59],"applications":[60],"such":[61,150],"as":[62,151],"target":[63],"detection":[64],"classification.":[66],"In":[67],"paper,":[69],"we":[70],"propose":[71],"usage":[73],"three":[75],"single":[76],"image":[77,95,110],"super-resolution":[78,116],"methods,":[79],"SRResNet,":[80],"EDSR,":[81],"WDSR,":[83],"for":[84],"resolution":[86,123],"enhancement":[87],"images.":[91],"First,":[92],"subsampled":[97],"factor":[99],"4":[101],"along":[102],"both":[103],"spatial":[104],"axes,":[105],"then":[107],"with":[113],"JPEG2000.":[114],"Finally,":[115],"methods":[117],"performed":[119],"to":[120,180],"improve":[121],"reduce":[125],"artifacts.":[128],"Experiments":[129],"were":[130],"carried":[131],"out":[132],"on":[133],"Onera":[135],"dataset":[136],"shared":[137],"by":[138],"IEEE":[139],"GRSS.":[140],"The":[141],"results":[142,165],"compared":[144,179],"terms":[146],"quality":[148,173],"metrics":[149,174],"signal-to-noise":[152],"ratios,":[153],"mean":[154],"spectral":[155,158],"angle,":[156,159],"maximum":[157,161],"absolute":[162],"difference.":[163],"Experimental":[164],"demonstrate":[166],"proposed":[169],"approaches":[170],"provide":[171],"higher":[172],"better":[176],"visual":[177],"performance":[178],"bicubic":[181],"upsampling.":[182]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}