{"id":"https://openalex.org/W3133388036","doi":"https://doi.org/10.1109/igarss39084.2020.9324350","title":"Shadow Detection in SAR Images: An OTSU- and CFAR-Based Method","display_name":"Shadow Detection in SAR Images: An OTSU- and CFAR-Based Method","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3133388036","doi":"https://doi.org/10.1109/igarss39084.2020.9324350","mag":"3133388036"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9324350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 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/A5101608037","display_name":"Haixiang Li","orcid":"https://orcid.org/0009-0004-7562-339X"},"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":"Hai-xiang Li","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101900861","display_name":"Xuelian Yu","orcid":"https://orcid.org/0000-0002-9577-3238"},"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":"Xue-lian Yu","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100554465","display_name":"Xindong Sun","orcid":null},"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":"Xin-dong Sun","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068192693","display_name":"Jinchuan Tian","orcid":"https://orcid.org/0000-0002-2129-471X"},"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":"Jin-chuan Tian","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050556614","display_name":"Xuegang Wang","orcid":"https://orcid.org/0000-0001-9008-5914"},"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":"Xue-gang Wang","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":3.179,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.93010189,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2803","last_page":"2806"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9998999834060669,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9998999834060669,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9994999766349792,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/shadow","display_name":"Shadow (psychology)","score":0.8319888710975647},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.811046302318573},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7253013849258423},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.7229353785514832},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.7176598906517029},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6790184378623962},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5717266798019409},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5330114960670471},{"id":"https://openalex.org/keywords/otsus-method","display_name":"Otsu's method","score":0.5319241285324097},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4861578643321991},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.4693886637687683},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4547114372253418},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4354630708694458}],"concepts":[{"id":"https://openalex.org/C117797892","wikidata":"https://www.wikidata.org/wiki/Q286363","display_name":"Shadow (psychology)","level":2,"score":0.8319888710975647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.811046302318573},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7253013849258423},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.7229353785514832},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.7176598906517029},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6790184378623962},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5717266798019409},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5330114960670471},{"id":"https://openalex.org/C21729346","wikidata":"https://www.wikidata.org/wiki/Q2444417","display_name":"Otsu's method","level":4,"score":0.5319241285324097},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4861578643321991},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.4693886637687683},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4547114372253418},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4354630708694458},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss39084.2020.9324350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"},{"score":0.4099999964237213,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G231933381","display_name":null,"funder_award_id":"61806046","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W337832058","https://openalex.org/W2079192682","https://openalex.org/W2089879284","https://openalex.org/W2110571732","https://openalex.org/W2111525901","https://openalex.org/W2118116104","https://openalex.org/W2133059825","https://openalex.org/W2271462986","https://openalex.org/W2513639043","https://openalex.org/W2534517308","https://openalex.org/W2560182400","https://openalex.org/W2624169843","https://openalex.org/W6676284990","https://openalex.org/W6677996474"],"related_works":["https://openalex.org/W2389939771","https://openalex.org/W2893218741","https://openalex.org/W4390770175","https://openalex.org/W4392589133","https://openalex.org/W1983393909","https://openalex.org/W2040150569","https://openalex.org/W2468095590","https://openalex.org/W2132174924","https://openalex.org/W1911540634","https://openalex.org/W2013909972"],"abstract_inverted_index":{"Shadow":[0],"has":[1],"gradually":[2],"become":[3],"an":[4,65],"important":[5],"feature":[6],"in":[7,22,37],"current":[8],"synthetic":[9],"aperture":[10],"radar":[11],"interpretation,":[12],"while":[13],"shadow":[14,35,49,99,130],"detection":[15,36,100,131],"itself":[16],"seemingly":[17],"didn't":[18],"attract":[19],"enough":[20],"attention":[21],"the":[23,54,94,121],"past":[24],"research.":[25],"This":[26],"paper":[27],"contributes":[28],"to":[29,75,85,127],"propose":[30],"a":[31,59,82],"new":[32],"method":[33,72,112],"for":[34],"SAR":[38,56,129],"images.":[39],"Our":[40],"algorithm":[41,126],"is":[42,73],"divided":[43],"into":[44],"three":[45],"stages:":[46],"firstly,":[47],"suspected":[48,90],"areas":[50,88],"are":[51,97],"extracted":[52],"from":[53,89,106],"input":[55],"image":[57],"with":[58],"dual-threshold":[60],"OTSU":[61],"based":[62,103],"segmentation;":[63],"secondly,":[64],"improved":[66],"two":[67],"parameter-constant":[68],"false":[69,87],"alarm":[70],"rate":[71],"utilized":[74],"detect":[76],"objects;":[77],"at":[78],"last,":[79],"we":[80],"design":[81],"discrimination":[83],"strategy":[84],"remove":[86],"shadows,":[91],"and":[92],"then":[93],"left":[95],"regions":[96],"final":[98],"results.":[101],"Experiments":[102],"on":[104],"images":[105],"MSTAR":[107],"dataset":[108],"present":[109],"that":[110],"our":[111,125],"comprehensively":[113],"outperforms":[114],"another":[115],"published":[116],"algorithm,":[117],"WD-CFAR,":[118],"which":[119],"demonstrates":[120],"feasibility":[122],"of":[123],"applying":[124],"practical":[128],"tasks.":[132]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
