{"id":"https://openalex.org/W1633763273","doi":"https://doi.org/10.1109/ijcnn.2015.7280481","title":"Filtering SAR imagery for edge detection using support value transform","display_name":"Filtering SAR imagery for edge detection using support value transform","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W1633763273","doi":"https://doi.org/10.1109/ijcnn.2015.7280481","mag":"1633763273"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2015.7280481","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2015.7280481","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Joint Conference on Neural Networks (IJCNN)","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/A5100425448","display_name":"Li Zhang","orcid":"https://orcid.org/0000-0001-7914-0679"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu, China","School of Computer Science and Technology, Soochow University, Suzhou 215006, Jiangsu, China)"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I3923682"]},{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou 215006, Jiangsu, China)","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100888103","display_name":"Weida Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148536","display_name":"Suzhou Electrical Apparatus Science Academy","ror":"https://ror.org/056tm2d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210148536"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weida Zhou","raw_affiliation_strings":["AI Speech Ltd., Suzhou, Jiangsu, China","AI Speech Ltd., Suzhou 215123, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"AI Speech Ltd., Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I4210148536"]},{"raw_affiliation_string":"AI Speech Ltd., Suzhou 215123, Jiangsu, China","institution_ids":["https://openalex.org/I4210148536"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075719824","display_name":"Bangjun Wang","orcid":"https://orcid.org/0000-0003-1372-2486"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bangjun Wang","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu, China","School of Computer Science and Technology, Soochow University, Suzhou 215006, Jiangsu, China)"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I3923682"]},{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou 215006, Jiangsu, China)","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100425448"],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":null,"apc_paid":null,"fwci":0.1841,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55684902,"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":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","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/T10688","display_name":"Image and Signal Denoising Methods","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":0.9991000294685364,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9990000128746033,"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/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.8443487286567688},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7842010855674744},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7138895988464355},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6665336489677429},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.6486776471138},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.619679868221283},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.5444186925888062},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4757777750492096},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.47432655096054077},{"id":"https://openalex.org/keywords/inverse-synthetic-aperture-radar","display_name":"Inverse synthetic aperture radar","score":0.4740143418312073},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4515756666660309},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.44687938690185547},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4417183995246887},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.30503663420677185},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.23210236430168152},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06925234198570251}],"concepts":[{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.8443487286567688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7842010855674744},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7138895988464355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6665336489677429},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.6486776471138},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.619679868221283},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.5444186925888062},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4757777750492096},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.47432655096054077},{"id":"https://openalex.org/C109094680","wikidata":"https://www.wikidata.org/wiki/Q6060432","display_name":"Inverse synthetic aperture radar","level":4,"score":0.4740143418312073},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4515756666660309},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.44687938690185547},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4417183995246887},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.30503663420677185},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.23210236430168152},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06925234198570251}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2015.7280481","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2015.7280481","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Joint Conference on Neural Networks (IJCNN)","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":39,"referenced_works":["https://openalex.org/W15951992","https://openalex.org/W1596717185","https://openalex.org/W1979063032","https://openalex.org/W1983101035","https://openalex.org/W1983461308","https://openalex.org/W1991972560","https://openalex.org/W2009104648","https://openalex.org/W2010853190","https://openalex.org/W2020880265","https://openalex.org/W2026849320","https://openalex.org/W2032805842","https://openalex.org/W2037813293","https://openalex.org/W2049909233","https://openalex.org/W2052491606","https://openalex.org/W2065578739","https://openalex.org/W2077567018","https://openalex.org/W2100604996","https://openalex.org/W2107053193","https://openalex.org/W2108883149","https://openalex.org/W2110571732","https://openalex.org/W2117294245","https://openalex.org/W2119077287","https://openalex.org/W2124520160","https://openalex.org/W2125384310","https://openalex.org/W2125517865","https://openalex.org/W2129038850","https://openalex.org/W2142572935","https://openalex.org/W2144494233","https://openalex.org/W2145023731","https://openalex.org/W2150399513","https://openalex.org/W2161736181","https://openalex.org/W2177509932","https://openalex.org/W3182176661","https://openalex.org/W4240744150","https://openalex.org/W4249617845","https://openalex.org/W6600659118","https://openalex.org/W6659679528","https://openalex.org/W6676284990","https://openalex.org/W6798649185"],"related_works":["https://openalex.org/W2065648684","https://openalex.org/W2113052720","https://openalex.org/W2799624451","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"],"abstract_inverted_index":{"Detecting":[0],"Edge":[1],"in":[2,25,45,87],"synthetic":[3],"aperture":[4],"radar":[5],"(SAR)":[6],"imagery":[7,27,47],"is":[8,117],"to":[9,100],"extract":[10,101],"contours":[11,103],"across":[12],"the":[13,29,79,84,88,92,102,105],"investigated":[14],"SAR":[15,26,46,60,89],"image.":[16,90,107],"Classical":[17],"edge":[18,43,94,114],"detection":[19,44,95,115],"methods":[20,96],"provide":[21],"a":[22,38,59,63,68],"limited":[23],"efficiency":[24],"for":[28,42],"presence":[30],"of":[31,70,104],"speckle":[32],"noise.":[33],"This":[34],"paper":[35],"deals":[36],"with":[37],"novel":[39,113],"filtering":[40],"method":[41],"based":[48],"on":[49],"support":[50,71],"value":[51,72],"transform":[52],"(SVT).":[53],"By":[54],"using":[55],"SVT,":[56],"we":[57],"decompose":[58],"image":[61,66,77],"into":[62],"low-frequency":[64,76,106],"component":[65],"and":[67],"series":[69],"images":[73],"(SVIs).":[74],"The":[75],"contains":[78],"slowly":[80],"variation":[81],"information,":[82],"or":[83],"contour":[85],"information":[86],"Then,":[91],"classical":[93],"can":[97],"be":[98],"used":[99],"Experimental":[108],"results":[109],"show":[110],"that":[111],"this":[112],"scheme":[116],"promising.":[118]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
