{"id":"https://openalex.org/W2986452373","doi":"https://doi.org/10.1109/igarss.2019.8900085","title":"PolSAR Image Edge Detection via Structure Tensor Analysis","display_name":"PolSAR Image Edge Detection via Structure Tensor Analysis","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2986452373","doi":"https://doi.org/10.1109/igarss.2019.8900085","mag":"2986452373"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8900085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8900085","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":"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/A5026771763","display_name":"Xiangrong Liu","orcid":"https://orcid.org/0000-0001-9885-1978"},"institutions":[{"id":"https://openalex.org/I4210119692","display_name":"Numerical Method (China)","ror":"https://ror.org/02ns8zp42","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210119692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangrong Liu","raw_affiliation_strings":["National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics, Beijing, China","institution_ids":["https://openalex.org/I4210119692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112956788","display_name":"Wei Mao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119692","display_name":"Numerical Method (China)","ror":"https://ror.org/02ns8zp42","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210119692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Mao","raw_affiliation_strings":["National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics, Beijing, China","institution_ids":["https://openalex.org/I4210119692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015235929","display_name":"Shunsheng Zhang","orcid":"https://orcid.org/0000-0002-5708-9240"},"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":"Shunsheng Zhang","raw_affiliation_strings":["Sch. of Info. Comm. Engin., University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sch. of Info. Comm. Engin., University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065178474","display_name":"Lei Wu","orcid":"https://orcid.org/0000-0003-1675-5283"},"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":"Lei Wu","raw_affiliation_strings":["Sch. of Info. Comm. Engin., University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sch. of Info. Comm. Engin., University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049463786","display_name":"Wen-Qin Wang","orcid":"https://orcid.org/0000-0003-4466-9585"},"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":"Wen-Qin Wang","raw_affiliation_strings":["Sch. of Info. Comm. Engin., University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sch. of Info. Comm. Engin., University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12831656,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"3269","last_page":"3272"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9983999729156494,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9983999729156494,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9943000078201294,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9915000200271606,"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/weighting","display_name":"Weighting","score":0.9057546854019165},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6507982611656189},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6416732668876648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5915266871452332},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.5893272757530212},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5673945546150208},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.5385267734527588},{"id":"https://openalex.org/keywords/structure-tensor","display_name":"Structure tensor","score":0.5377986431121826},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5044597387313843},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.46176284551620483},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.4511498808860779},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4145439863204956},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3856527805328369},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2646656036376953},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.21248483657836914},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06754738092422485},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.059978365898132324},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.05286511778831482}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.9057546854019165},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6507982611656189},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6416732668876648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5915266871452332},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.5893272757530212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5673945546150208},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.5385267734527588},{"id":"https://openalex.org/C113315163","wikidata":"https://www.wikidata.org/wiki/Q7625159","display_name":"Structure tensor","level":3,"score":0.5377986431121826},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5044597387313843},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.46176284551620483},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.4511498808860779},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4145439863204956},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3856527805328369},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2646656036376953},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.21248483657836914},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06754738092422485},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.059978365898132324},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.05286511778831482},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2019.8900085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8900085","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.41999998688697815,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W84374482","https://openalex.org/W89301254","https://openalex.org/W2092335158","https://openalex.org/W2107432971","https://openalex.org/W2113834179","https://openalex.org/W2115036262","https://openalex.org/W2116211213","https://openalex.org/W2123491786","https://openalex.org/W2141498692","https://openalex.org/W2147469781","https://openalex.org/W2159989013","https://openalex.org/W2313344562","https://openalex.org/W6603484826"],"related_works":["https://openalex.org/W89301254","https://openalex.org/W2623954137","https://openalex.org/W2535084101","https://openalex.org/W2015754241","https://openalex.org/W1997494252","https://openalex.org/W3174244707","https://openalex.org/W3206725971","https://openalex.org/W2944675036","https://openalex.org/W2052072320","https://openalex.org/W2385280846"],"abstract_inverted_index":{"The":[0,22],"weighted":[1],"structure":[2],"tensor":[3],"(ST)":[4],"can":[5],"be":[6,57],"usually":[7],"used":[8],"on":[9,101],"edge":[10,36,49,62,102],"detection":[11],"of":[12,48,64,81],"multi-channel":[13,66],"images,":[14],"including":[15],"polarimetric":[16],"synthetic":[17],"aperture":[18],"radar":[19],"(polSAR)":[20],"images.":[21,67],"traditional":[23,53,99],"weighting":[24,54,73],"method":[25,55,74,96,100],"is":[26,84],"average":[27],"weighting,":[28],"each":[29,82],"channel":[30,83],"considered":[31],"to":[32,44,59],"provide":[33],"the":[34,52,65,79,87,94,98],"same":[35],"information.":[37],"But":[38],"in":[39,77],"fact":[40],"different":[41,46],"channels":[42],"tend":[43],"contain":[45],"amount":[47],"information,":[50],"so":[51],"cannot":[56],"adopted":[58],"extract":[60],"full":[61],"information":[63],"This":[68],"letter":[69],"proposes":[70],"a":[71],"novel":[72],"for":[75],"ST,":[76],"which":[78],"weight":[80],"obtained":[85],"by":[86],"eigenvalue-measured":[88],"way.":[89],"Experimental":[90],"results":[91],"show":[92],"that":[93],"proposed":[95],"outperforms":[97],"detection.":[103]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}