{"id":"https://openalex.org/W4382137505","doi":"https://doi.org/10.3390/rs15133251","title":"Level Sets Guided by SoDEF-Fitting Energy for River Channel Detection in SAR Images","display_name":"Level Sets Guided by SoDEF-Fitting Energy for River Channel Detection in SAR Images","publication_year":2023,"publication_date":"2023-06-24","ids":{"openalex":"https://openalex.org/W4382137505","doi":"https://doi.org/10.3390/rs15133251"},"language":"en","primary_location":{"id":"doi:10.3390/rs15133251","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15133251","pdf_url":"https://www.mdpi.com/2072-4292/15/13/3251/pdf?version=1687594704","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/13/3251/pdf?version=1687594704","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Bin Han","orcid":"https://orcid.org/0009-0006-3532-324X"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bin Han","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China"],"raw_orcid":"https://orcid.org/0009-0006-3532-324X","affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054810403","display_name":"Anup Basu","orcid":"https://orcid.org/0000-0002-7695-4148"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Anup Basu","raw_affiliation_strings":["Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada"],"raw_orcid":"https://orcid.org/0000-0002-7695-4148","affiliations":[{"raw_affiliation_string":"Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada","institution_ids":["https://openalex.org/I154425047"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.2127,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.47584694,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"15","issue":"13","first_page":"3251","last_page":"3251"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9919999837875366,"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":0.9919999837875366,"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/T10330","display_name":"Hydrology and Watershed Management Studies","score":0.9789000153541565,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9761000275611877,"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":0.6709961891174316},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6417960524559021},{"id":"https://openalex.org/keywords/quadratic-function","display_name":"Quadratic function","score":0.5835127830505371},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5040897130966187},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.5001001358032227},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.48026227951049805},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.4757792055606842},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4743852913379669},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.45283743739128113},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4341093897819519},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40547794103622437},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.39393407106399536},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.3553151488304138},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3104228079319},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23366180062294006},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1407260000705719},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10615965723991394},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08315914869308472}],"concepts":[{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6709961891174316},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6417960524559021},{"id":"https://openalex.org/C166437778","wikidata":"https://www.wikidata.org/wiki/Q50695","display_name":"Quadratic function","level":3,"score":0.5835127830505371},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5040897130966187},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.5001001358032227},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.48026227951049805},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.4757792055606842},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4743852913379669},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.45283743739128113},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4341093897819519},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40547794103622437},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.39393407106399536},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.3553151488304138},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3104228079319},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23366180062294006},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1407260000705719},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10615965723991394},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08315914869308472},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15133251","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15133251","pdf_url":"https://www.mdpi.com/2072-4292/15/13/3251/pdf?version=1687594704","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:165d6655dbbd497591831f58bdf27de8","is_oa":true,"landing_page_url":"https://doaj.org/article/165d6655dbbd497591831f58bdf27de8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 13, p 3251 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/13/3251/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15133251","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 15; Issue 13; Pages: 3251","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15133251","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15133251","pdf_url":"https://www.mdpi.com/2072-4292/15/13/3251/pdf?version=1687594704","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7650832904","display_name":null,"funder_award_id":"BK20220392","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G8104128920","display_name":null,"funder_award_id":"62201281","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"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4382137505.pdf"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1424614812","https://openalex.org/W2009767800","https://openalex.org/W2018563981","https://openalex.org/W2057939005","https://openalex.org/W2116040950","https://openalex.org/W2139478903","https://openalex.org/W2233053992","https://openalex.org/W2237816386","https://openalex.org/W2287927567","https://openalex.org/W2507679505","https://openalex.org/W2608836634","https://openalex.org/W2789357860","https://openalex.org/W2789609908","https://openalex.org/W2792527658","https://openalex.org/W2794304857","https://openalex.org/W2800561367","https://openalex.org/W2803282406","https://openalex.org/W2807700654","https://openalex.org/W2808829191","https://openalex.org/W2809931234","https://openalex.org/W2883218616","https://openalex.org/W2885194677","https://openalex.org/W2885353400","https://openalex.org/W2888621818","https://openalex.org/W2904933464","https://openalex.org/W2942864978","https://openalex.org/W2966505783","https://openalex.org/W2988949830","https://openalex.org/W3003805783","https://openalex.org/W3038044614","https://openalex.org/W3082365061","https://openalex.org/W3122877105","https://openalex.org/W3125389357","https://openalex.org/W3129902988","https://openalex.org/W3130997388","https://openalex.org/W3132093070","https://openalex.org/W3132378062","https://openalex.org/W3132614832","https://openalex.org/W3137254647","https://openalex.org/W3141826546","https://openalex.org/W3152007055","https://openalex.org/W3157649829","https://openalex.org/W3159946139","https://openalex.org/W3169078176","https://openalex.org/W3170029376","https://openalex.org/W3173559883","https://openalex.org/W3210789979"],"related_works":["https://openalex.org/W269925151","https://openalex.org/W3096788047","https://openalex.org/W2101513891","https://openalex.org/W2075961230","https://openalex.org/W4386731488","https://openalex.org/W2024156986","https://openalex.org/W2995216836","https://openalex.org/W4385817362","https://openalex.org/W2765709060","https://openalex.org/W4320232412"],"abstract_inverted_index":{"To":[0],"achieve":[1],"river":[2,125],"channel":[3,126],"detection":[4,127,148],"in":[5,87,146],"SAR":[6,132],"(synthetic":[7],"aperture":[8],"radar)":[9],"images,":[10],"we":[11,35],"developed":[12,137],"a":[13,19,37],"level-set-based":[14],"model":[15,138],"(LSBM)":[16],"guided":[17],"by":[18,39,93],"designed":[20,36],"data-fitting":[21,59],"energy":[22],"which":[23,76],"is":[24,139],"called":[25],"the":[26,41,50,58,62,84,100,106,116,121,136,142],"SoDEF":[27],"(sum":[28],"of":[29,43,73],"dual":[30,44],"exponential":[31,45],"functions)-fitting":[32],"energy.":[33,60],"Firstly,":[34],"function":[38,86,97,118],"computing":[40],"sum":[42],"functions":[46],"to":[47,56,98,119,141],"substitute":[48],"for":[49],"quadratic":[51],"function,":[52],"and":[53,80,150],"used":[54],"it":[55],"construct":[57],"Secondly,":[61],"adaptive":[63],"area-fitting":[64],"centers":[65],"(AFCs)":[66],"were":[67,113],"computed":[68],"based":[69],"on":[70],"two":[71],"kinds":[72],"grayscale":[74],"characteristics,":[75],"are":[77],"more":[78,81],"accurate":[79],"stable.":[82],"Thirdly,":[83],"Dirac":[85],"gradient":[88],"descent":[89],"flow":[90],"was":[91],"displaced":[92],"an":[94],"edge":[95],"indicator":[96],"help":[99],"evolving":[101],"level":[102],"sets":[103],"stop":[104],"at":[105],"target":[107],"edges.":[108],"Moreover,":[109],"some":[110],"regularized":[111],"terms":[112],"incorporated":[114],"into":[115],"objective":[117],"guarantee":[120],"model\u2019s":[122],"stability.":[123],"The":[124],"experiments":[128],"conducted":[129],"with":[130],"real":[131],"images":[133],"indicated":[134],"that":[135],"superior":[140],"related":[143],"state-of-the-art":[144],"methods":[145],"its":[147],"accuracy":[149],"efficiency.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}