{"id":"https://openalex.org/W1968419435","doi":"https://doi.org/10.1109/lgrs.2013.2286089","title":"Curvelet-Based Synthetic Aperture Radar Image Classification","display_name":"Curvelet-Based Synthetic Aperture Radar Image Classification","publication_year":2013,"publication_date":"2013-11-19","ids":{"openalex":"https://openalex.org/W1968419435","doi":"https://doi.org/10.1109/lgrs.2013.2286089","mag":"1968419435"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2013.2286089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2013.2286089","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5008200304","display_name":"Erkan Uslu","orcid":"https://orcid.org/0000-0002-6971-981X"},"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":true,"raw_author_name":"Erkan Uslu","raw_affiliation_strings":["Computer Engineering Department, Yildiz Technical University, Istanbul, Turkey","Comput. Eng. Dept., Yildiz Tech. Univ., Istanbul, Turkey"],"affiliations":[{"raw_affiliation_string":"Computer Engineering Department, Yildiz Technical University, Istanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]},{"raw_affiliation_string":"Comput. Eng. Dept., Yildiz Tech. Univ., Istanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036755640","display_name":"Song\u00fcl Albayrak","orcid":"https://orcid.org/0000-0002-1786-6869"},"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":"Songul Albayrak","raw_affiliation_strings":["Computer Engineering Department, Yildiz Technical University, Istanbul, Turkey","Comput. Eng. Dept., Yildiz Tech. Univ., Istanbul, Turkey"],"affiliations":[{"raw_affiliation_string":"Computer Engineering Department, Yildiz Technical University, Istanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]},{"raw_affiliation_string":"Comput. Eng. Dept., Yildiz Tech. Univ., Istanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5008200304"],"corresponding_institution_ids":["https://openalex.org/I4101805"],"apc_list":null,"apc_paid":null,"fwci":9.5307,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.97279672,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"11","issue":"6","first_page":"1071","last_page":"1075"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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":0.9890000224113464,"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/T10535","display_name":"Landslides and related hazards","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/curvelet","display_name":"Curvelet","score":0.957892894744873},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7675062417984009},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6679235696792603},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6628608107566833},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.6542431116104126},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6502278447151184},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6448626518249512},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5999441146850586},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.5806028842926025},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.496737539768219},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4907895028591156},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.4742012619972229},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4593532383441925},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.42708587646484375},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.3033864498138428},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.20903226733207703},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2016436755657196},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.11747622489929199}],"concepts":[{"id":"https://openalex.org/C131720326","wikidata":"https://www.wikidata.org/wiki/Q5196075","display_name":"Curvelet","level":4,"score":0.957892894744873},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7675062417984009},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6679235696792603},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6628608107566833},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.6542431116104126},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6502278447151184},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6448626518249512},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5999441146850586},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.5806028842926025},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.496737539768219},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4907895028591156},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.4742012619972229},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4593532383441925},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.42708587646484375},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.3033864498138428},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.20903226733207703},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2016436755657196},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.11747622489929199},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2013.2286089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2013.2286089","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G8032991345","display_name":null,"funder_award_id":"2011-04-01-DOP01","funder_id":"https://openalex.org/F4320323955","funder_display_name":"Yildiz Teknik \u00dcniversitesi"}],"funders":[{"id":"https://openalex.org/F4320323955","display_name":"Yildiz Teknik \u00dcniversitesi","ror":"https://ror.org/0547yzj13"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1891956733","https://openalex.org/W2018775529","https://openalex.org/W2064108454","https://openalex.org/W2066512559","https://openalex.org/W2095595743","https://openalex.org/W2130094715","https://openalex.org/W2131427747","https://openalex.org/W2143353454","https://openalex.org/W2147497470","https://openalex.org/W2156580010"],"related_works":["https://openalex.org/W2065648684","https://openalex.org/W2009383287","https://openalex.org/W2042914788","https://openalex.org/W2182190754","https://openalex.org/W4321264664","https://openalex.org/W2055824452","https://openalex.org/W2121688719","https://openalex.org/W2727313114","https://openalex.org/W2016481886","https://openalex.org/W2011306163"],"abstract_inverted_index":{"Curvelet":[0],"transform":[1,7],"(CT)":[2],"is":[3,25,57,66,81,139],"a":[4,82],"multiscale":[5],"directional":[6],"that":[8,85,135],"enables":[9],"the":[10,87,99],"use":[11,41,88],"of":[12,45,89,95],"texture":[13],"and":[14,59,65,121],"spatial":[15],"locality":[16],"information.":[17],"In":[18],"synthetic":[19],"aperture":[20],"radar":[21],"(SAR)":[22],"imaging,":[23],"CT":[24,35],"mostly":[26],"used":[27,60],"in":[28,39,61],"speckle":[29,143],"noise":[30],"reduction.":[31],"This":[32],"letter":[33],"utilizes":[34,86],"for":[36,52,74],"feature":[37,47,102,137],"extraction":[38,48,103,138],"land":[40],"classification.":[42],"Two":[43],"types":[44],"curvelet-based":[46,101,136],"methods":[49],"are":[50,115],"implemented":[51],"SAR.":[53],"The":[54,78],"first":[55],"one":[56],"defined":[58],"content-based":[62],"image":[63],"retrieval":[64],"based":[67],"on":[68,106],"generalized":[69],"Gaussian":[70],"distribution":[71],"parameter":[72],"estimation":[73],"each":[75],"curvelet":[76,90],"subband.":[77],"second":[79],"implementation":[80],"genuine":[83],"method":[84,104],"subband":[91],"histograms,":[92],"namely,":[93],"histogram":[94],"curvelets":[96],"(HoC).":[97],"Using":[98],"proposed":[100],"(HoC)":[105],"SAR":[107],"data,":[108],"better":[109],"classification":[110,129],"accuracies":[111],"up":[112],"to":[113,118,126],"99.56%":[114],"achieved":[116],"compared":[117],"original":[119],"data":[120,128],"H/A/\u03b1":[122],"decomposition":[123],"features.":[124],"Compared":[125],"speckle-noise-reduced":[127],"results,":[130],"it":[131],"can":[132],"be":[133],"said":[134],"also":[140],"robust":[141],"against":[142],"noise.":[144]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}