{"id":"https://openalex.org/W2973472829","doi":"https://doi.org/10.1109/lgrs.2019.2937355","title":"Oil Tank Extraction Based on Joint-Spatial Saliency Analysis for Multiple SAR Images","display_name":"Oil Tank Extraction Based on Joint-Spatial Saliency Analysis for Multiple SAR Images","publication_year":2019,"publication_date":"2019-09-17","ids":{"openalex":"https://openalex.org/W2973472829","doi":"https://doi.org/10.1109/lgrs.2019.2937355","mag":"2973472829"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2019.2937355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2937355","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/A5087779583","display_name":"Libao Zhang","orcid":"https://orcid.org/0000-0002-0888-2330"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Libao Zhang","raw_affiliation_strings":["College of Information Science and Technology, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102848466","display_name":"Congyang Liu","orcid":"https://orcid.org/0009-0004-9431-4445"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Congyang Liu","raw_affiliation_strings":["College of Information Science and Technology, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087779583"],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":null,"apc_paid":null,"fwci":0.613,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.72864417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"17","issue":"6","first_page":"998","last_page":"1002"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","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/T11605","display_name":"Visual Attention and Saliency Detection","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":0.9950000047683716,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9940999746322632,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7744879722595215},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.707737147808075},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6837495565414429},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6406652927398682},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.6225222945213318},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5614397525787354},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5466088652610779},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5391921997070312},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5265757441520691},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5111728310585022},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5034851431846619},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.4942329227924347},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.2266044318675995},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12028813362121582}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7744879722595215},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.707737147808075},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6837495565414429},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6406652927398682},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.6225222945213318},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5614397525787354},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5466088652610779},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5391921997070312},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5265757441520691},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5111728310585022},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5034851431846619},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.4942329227924347},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.2266044318675995},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12028813362121582},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2019.2937355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2937355","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":[],"awards":[{"id":"https://openalex.org/G3872703625","display_name":null,"funder_award_id":"41771407","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5547827018","display_name":null,"funder_award_id":"61571050","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6448652067","display_name":null,"funder_award_id":"L182029","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":21,"referenced_works":["https://openalex.org/W1992992668","https://openalex.org/W2002631607","https://openalex.org/W2003086251","https://openalex.org/W2004376198","https://openalex.org/W2043539028","https://openalex.org/W2055093645","https://openalex.org/W2059817405","https://openalex.org/W2073459066","https://openalex.org/W2088167233","https://openalex.org/W2096982104","https://openalex.org/W2112328181","https://openalex.org/W2118246710","https://openalex.org/W2128098741","https://openalex.org/W2133059825","https://openalex.org/W2146103513","https://openalex.org/W2162633365","https://openalex.org/W2241675565","https://openalex.org/W2331427273","https://openalex.org/W2403333215","https://openalex.org/W2901242031","https://openalex.org/W6668990524"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W1981531423","https://openalex.org/W4394861761","https://openalex.org/W1977371217","https://openalex.org/W2035264131","https://openalex.org/W1679012645","https://openalex.org/W1925461966"],"abstract_inverted_index":{"The":[0,96,135,168,186],"lack":[1,114],"of":[2,8,15,112,115,123,127,137,153,162,173,188],"true":[3,116],"color":[4],"and":[5,69,76,84,106,142,182],"the":[6,12,16,24,43,53,66,81,85,93,101,110,113,121,124,130,143,151,154,158,160,163,171,174,179,183,189,195,203],"presence":[7],"background":[9],"clutter":[10],"reduce":[11],"accuracy":[13,196],"rate":[14],"saliency":[17,45,60,128,144],"analysis":[18,46,55],"for":[19,48],"oil":[20,40,164],"tank":[21],"extraction":[22],"in":[23,92,177],"synthetic":[25],"aperture":[26],"radar":[27],"(SAR)":[28],"images.":[29,51],"This":[30,64],"letter":[31],"proposes":[32],"a":[33,59,73],"specially":[34],"designed":[35],"unsupervised":[36],"method":[37,176],"to":[38,108,119,193],"extract":[39],"tanks":[41,165],"using":[42],"joint-spatial":[44],"(JSSA)":[47],"multiple":[49],"SAR":[50],"First,":[52],"intrasaliency":[54],"is":[56,133,166],"established":[57],"on":[58],"driven":[61],"iterative":[62],"clustering.":[63],"considers":[65],"spatial":[67],"intensity":[68],"texture":[70],"feature":[71],"within":[72,157],"single":[74],"image":[75],"suppresses":[77],"most":[78],"backgrounds.":[79],"Second,":[80],"cospatial":[82],"residual":[83],"local":[86],"grayscale":[87],"statistics":[88,152],"are":[89,104,140,146],"considered":[90],"independently":[91],"intersaliency":[94],"analysis.":[95],"common":[97],"salient":[98],"parts":[99],"among":[100],"input":[102],"series":[103],"extracted":[105],"used":[107],"overcome":[109],"problem":[111],"color.":[117],"Third,":[118],"make":[120],"fusion":[122],"two":[125],"kinds":[126],"maps,":[129],"low-rank":[131],"matrix":[132],"introduced.":[134],"weights":[136],"different":[138],"maps":[139],"calculated":[141],"cues":[145],"integrated":[147],"efficiently.":[148],"Finally,":[149],"after":[150],"highlight":[155],"points":[156],"candidates,":[159],"location":[161],"refined.":[167],"experiments":[169],"show":[170],"superiority":[172],"proposed":[175],"both":[178],"pixel":[180],"level":[181],"geometric":[184],"segmentation.":[185],"result":[187],"JSSA":[190],"model":[191],"appears":[192],"improve":[194],"with":[197,202],"fewer":[198],"missing":[199],"objects":[200],"compared":[201],"competing":[204],"algorithms.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}