{"id":"https://openalex.org/W2993444638","doi":"https://doi.org/10.1109/access.2019.2957387","title":"An Efficient Variational-Level-Set Model Based on Adaptive Local Fitted Image for Noisy Image Segmentation","display_name":"An Efficient Variational-Level-Set Model Based on Adaptive Local Fitted Image for Noisy Image Segmentation","publication_year":2019,"publication_date":"2019-12-03","ids":{"openalex":"https://openalex.org/W2993444638","doi":"https://doi.org/10.1109/access.2019.2957387","mag":"2993444638"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2957387","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2957387","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08920073.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08920073.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071206451","display_name":"Cheng Liu","orcid":"https://orcid.org/0000-0001-8382-191X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Liu","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8382-191X","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101917066","display_name":"Weibin Liu","orcid":"https://orcid.org/0000-0001-6246-0051"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weibin Liu","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6246-0051","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007723033","display_name":"Weiwei Xing","orcid":"https://orcid.org/0000-0002-6378-926X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Xing","raw_affiliation_strings":["School of Software Engineering, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6378-926X","affiliations":[{"raw_affiliation_string":"School of Software Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.14494261,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"8","issue":null,"first_page":"17500","last_page":"17526"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9993000030517578,"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":0.9993000030517578,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9797999858856201,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9747999906539917,"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/image-segmentation","display_name":"Image segmentation","score":0.7108514308929443},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.6607792973518372},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6584125757217407},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.6353242993354797},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6132614016532898},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5818804502487183},{"id":"https://openalex.org/keywords/energy-functional","display_name":"Energy functional","score":0.49236905574798584},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.47265851497650146},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4555181562900543},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.44398176670074463},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4427414536476135},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.4318270683288574},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.42551618814468384},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.41619569063186646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39639854431152344},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3137238025665283},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2736479640007019}],"concepts":[{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.7108514308929443},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.6607792973518372},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6584125757217407},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.6353242993354797},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6132614016532898},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5818804502487183},{"id":"https://openalex.org/C191640071","wikidata":"https://www.wikidata.org/wiki/Q5377056","display_name":"Energy functional","level":2,"score":0.49236905574798584},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.47265851497650146},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4555181562900543},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.44398176670074463},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4427414536476135},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.4318270683288574},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.42551618814468384},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.41619569063186646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39639854431152344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3137238025665283},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2736479640007019},{"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2957387","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2957387","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08920073.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:63e2f2b29d884ef8a5ec9229cdf2bc18","is_oa":true,"landing_page_url":"https://doaj.org/article/63e2f2b29d884ef8a5ec9229cdf2bc18","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":"IEEE Access, Vol 8, Pp 17500-17526 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2957387","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2957387","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08920073.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8100000023841858}],"awards":[{"id":"https://openalex.org/G1907528026","display_name":null,"funder_award_id":"61976017","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G210926631","display_name":null,"funder_award_id":"61876018","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":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2993444638.pdf","grobid_xml":"https://content.openalex.org/works/W2993444638.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W243024380","https://openalex.org/W267311712","https://openalex.org/W752953485","https://openalex.org/W1510047790","https://openalex.org/W1979393293","https://openalex.org/W1987286789","https://openalex.org/W1989135034","https://openalex.org/W1989532447","https://openalex.org/W1995911388","https://openalex.org/W2009767800","https://openalex.org/W2012276822","https://openalex.org/W2029225029","https://openalex.org/W2036576620","https://openalex.org/W2038495454","https://openalex.org/W2074620982","https://openalex.org/W2081203777","https://openalex.org/W2082370554","https://openalex.org/W2082833656","https://openalex.org/W2104095591","https://openalex.org/W2116040950","https://openalex.org/W2132116135","https://openalex.org/W2138047924","https://openalex.org/W2139478903","https://openalex.org/W2145596983","https://openalex.org/W2159152281","https://openalex.org/W2214821036","https://openalex.org/W2216748439","https://openalex.org/W2320230300","https://openalex.org/W2433693374","https://openalex.org/W2467514263","https://openalex.org/W2554820184","https://openalex.org/W2560385169","https://openalex.org/W2586834759","https://openalex.org/W2591232542","https://openalex.org/W2732931556","https://openalex.org/W2735229802","https://openalex.org/W2789854811","https://openalex.org/W2792834173","https://openalex.org/W2794082735","https://openalex.org/W2800561367","https://openalex.org/W2803524673","https://openalex.org/W2810753213","https://openalex.org/W2892118665","https://openalex.org/W2906293839","https://openalex.org/W2907398861","https://openalex.org/W3211330693"],"related_works":["https://openalex.org/W2204605857","https://openalex.org/W3196005494","https://openalex.org/W2355370993","https://openalex.org/W2093085045","https://openalex.org/W2170380303","https://openalex.org/W1996489018","https://openalex.org/W2069318476","https://openalex.org/W2184524617","https://openalex.org/W2115198604","https://openalex.org/W2131637713"],"abstract_inverted_index":{"In":[0],"image":[1,6,32,57,73,106,110,180,216],"processing":[2],"and":[3,27,44,66,76,145,173,190,205],"computer":[4],"vision,":[5],"segmentation":[7,39,124],"plays":[8],"a":[9,92],"fundamental":[10],"role":[11],"since":[12],"it":[13],"can":[14,142,154,169],"make":[15],"images":[16,26,43,193],"easier":[17],"to":[18,31,58,82,97,119,202],"analyze.":[19],"However,":[20],"noise":[21,149],"is":[22,74,95,132,165,199],"easily":[23],"introduced":[24,77,133],"into":[25,78,134],"brings":[28],"great":[29],"challenges":[30],"segmentation.":[33,181,217],"This":[34],"paper":[35],"focuses":[36],"on":[37,53,150,184],"the":[38,79,84,87,99,102,108,113,121,127,135,138,146,151,162,171,196],"problem":[40],"of":[41,86,101,123,148,161,207],"noisy":[42,179,215],"proposes":[45],"an":[46,69],"efficient":[47],"variational":[48,129],"level":[49,139],"set":[50,140],"model":[51,88,164,198],"based":[52],"adaptive":[54,70,103],"local":[55,64,67,71,104],"fitted":[56,72,105],"handle":[59],"it.":[60],"By":[61],"utilizing":[62],"normalized":[63],"entropy":[65],"means,":[68],"proposed":[75,96,197],"data":[80],"term":[81,94,131],"enhance":[83],"robustness":[85],"against":[89],"noise.":[90],"Then":[91],"penalty":[93],"reduce":[98],"deviation":[100],"from":[107],"original":[109],"by":[111],"punishing":[112],"difference":[114],"between":[115],"them,":[116],"so":[117,137],"as":[118],"guarantee":[120],"accuracy":[122],"results.":[125],"Later,":[126],"total":[128],"regularization":[130],"model,":[136],"function":[141],"be":[143,155],"smoothed":[144],"effect":[147],"active":[152],"contour":[153],"further":[156],"reduced.":[157],"The":[158],"energy":[159],"functional":[160],"whole":[163],"convex":[166],"rigorously,":[167],"which":[168,209],"reach":[170],"minimum":[172],"should":[174],"have":[175],"good":[176,212],"properties":[177],"in":[178,214],"Numerous":[182],"experiments":[183],"synthetic,":[185],"natural,":[186],"synthetic":[187],"aperture":[188],"radar":[189],"oil":[191],"spill":[192],"demonstrate":[194],"that":[195],"strongly":[200],"robust":[201],"different":[203],"types":[204],"levels":[206],"noise,":[208],"indicates":[210],"its":[211],"performance":[213]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}