{"id":"https://openalex.org/W2062271656","doi":"https://doi.org/10.1137/130920241","title":"A Two-Stage Image Segmentation Method for Blurry Images with Poisson or Multiplicative Gamma Noise","display_name":"A Two-Stage Image Segmentation Method for Blurry Images with Poisson or Multiplicative Gamma Noise","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2062271656","doi":"https://doi.org/10.1137/130920241","mag":"2062271656"},"language":"en","primary_location":{"id":"doi:10.1137/130920241","is_oa":false,"landing_page_url":"https://doi.org/10.1137/130920241","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","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/A5004126693","display_name":"Raymond H. Chan","orcid":"https://orcid.org/0000-0003-0910-4685"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Raymond Chan","raw_affiliation_strings":["Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021574704","display_name":"Hongfei Yang","orcid":"https://orcid.org/0000-0002-7016-8867"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Hongfei Yang","raw_affiliation_strings":["Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059443966","display_name":"Tieyong Zeng","orcid":"https://orcid.org/0000-0002-0688-202X"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Tieyong Zeng","raw_affiliation_strings":["Department of Mathematics"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004126693"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":5.9312,"has_fulltext":false,"cited_by_count":79,"citation_normalized_percentile":{"value":0.97093791,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"7","issue":"1","first_page":"98","last_page":"127"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9977999925613403,"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/segmentation","display_name":"Segmentation","score":0.6860845685005188},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.6070272326469421},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5556153655052185},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5484739542007446},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5446022748947144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49630647897720337},{"id":"https://openalex.org/keywords/multiplicative-function","display_name":"Multiplicative function","score":0.4841693043708801},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4678889811038971},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.4448007345199585},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.43123000860214233},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42730244994163513},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.41184669733047485},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40712597966194153},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36412590742111206},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3150784969329834},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.137428879737854},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1052480936050415},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08301466703414917}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6860845685005188},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.6070272326469421},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5556153655052185},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5484739542007446},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5446022748947144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49630647897720337},{"id":"https://openalex.org/C42747912","wikidata":"https://www.wikidata.org/wiki/Q1048447","display_name":"Multiplicative function","level":2,"score":0.4841693043708801},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4678889811038971},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.4448007345199585},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.43123000860214233},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42730244994163513},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.41184669733047485},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40712597966194153},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36412590742111206},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3150784969329834},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.137428879737854},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1052480936050415},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08301466703414917},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1137/130920241","is_oa":false,"landing_page_url":"https://doi.org/10.1137/130920241","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.414.4206","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.414.4206","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.math.cuhk.edu.hk/~rchan/paper/tieyong-hongfei_poisson.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.432.8860","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.432.8860","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.math.cuhk.edu.hk/~rchan/paper/tieyong-hongfei_poisson.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1498640224","https://openalex.org/W1968309215","https://openalex.org/W1977556410","https://openalex.org/W1985349496","https://openalex.org/W1985588167","https://openalex.org/W1986850130","https://openalex.org/W1991139668","https://openalex.org/W1992719146","https://openalex.org/W1998339281","https://openalex.org/W1998683784","https://openalex.org/W2000396646","https://openalex.org/W2001806704","https://openalex.org/W2003063671","https://openalex.org/W2004260841","https://openalex.org/W2006919211","https://openalex.org/W2008794074","https://openalex.org/W2010825468","https://openalex.org/W2010840867","https://openalex.org/W2011083450","https://openalex.org/W2011516671","https://openalex.org/W2021262032","https://openalex.org/W2026269844","https://openalex.org/W2038495454","https://openalex.org/W2042597321","https://openalex.org/W2049607297","https://openalex.org/W2065267700","https://openalex.org/W2071005004","https://openalex.org/W2090390875","https://openalex.org/W2092663520","https://openalex.org/W2100533333","https://openalex.org/W2103559027","https://openalex.org/W2105125008","https://openalex.org/W2110264793","https://openalex.org/W2113726946","https://openalex.org/W2114487471","https://openalex.org/W2116040950","https://openalex.org/W2121927366","https://openalex.org/W2122890444","https://openalex.org/W2140843581","https://openalex.org/W2142058898","https://openalex.org/W2143015120","https://openalex.org/W2144751639","https://openalex.org/W2148395215","https://openalex.org/W2148791483","https://openalex.org/W2155280009","https://openalex.org/W2159152281","https://openalex.org/W2161160262","https://openalex.org/W2165734775","https://openalex.org/W2172029033","https://openalex.org/W2944437997","https://openalex.org/W4236965008","https://openalex.org/W4256051666","https://openalex.org/W4292363360"],"related_works":["https://openalex.org/W1968965685","https://openalex.org/W2012792772","https://openalex.org/W2356573839","https://openalex.org/W2009028679","https://openalex.org/W2357424838","https://openalex.org/W2356903262","https://openalex.org/W2327601824","https://openalex.org/W4237142086","https://openalex.org/W2161102362","https://openalex.org/W2106833984"],"abstract_inverted_index":{"In":[0,136],"this":[1],"paper,":[2],"a":[3,26,52,57],"two-stage":[4,30,172],"method":[5,22,48,173],"for":[6,184],"segmenting":[7],"blurry":[8],"images":[9],"in":[10,104],"the":[11,33,41,61,65,83,88,91,94,97,105,108,124,158],"presence":[12],"of":[13,35,46,60,90,96],"Poisson":[14],"or":[15,126,157,180],"multiplicative":[16],"Gamma":[17],"noise":[18],"is":[19,23,49,69,78,102,110,153],"proposed.":[20],"The":[21,43,118],"inspired":[24],"by":[25,71,112,123,131,147],"previous":[27],"work":[28],"on":[29],"segmentation":[31,109,144,182],"and":[32,93,194],"usage":[34],"an":[36,72],"I-divergence":[37,73],"term":[38,68],"to":[39,50,56,80,164],"handle":[40],"noise.":[42],"first":[44],"stage":[45],"our":[47,137,171],"find":[51],"smooth":[53],"solution":[54,98],"$u$":[55,101,114,152,163],"convex":[58],"variant":[59],"Mumford--Shah":[62],"model":[63],"where":[64],"$\\ell_2$":[66],"data-fidelity":[67],"replaced":[70],"term.":[74],"A":[75],"primal-dual":[76],"algorithm":[77,92],"adopted":[79],"efficiently":[81],"solve":[82],"minimization":[84],"problem.":[85],"We":[86],"prove":[87],"convergence":[89],"uniqueness":[95],"$u$.":[99],"Once":[100],"obtained,":[103],"second":[106],"stage,":[107],"done":[111],"thresholding":[113],"into":[115],"different":[116],"phases.":[117],"thresholds":[119,150,159],"can":[120,127,140],"be":[121,128,165],"given":[122],"users":[125],"obtained":[129],"automatically":[130],"using":[132],"any":[133,142],"clustering":[134],"method.":[135],"method,":[138],"we":[139],"obtain":[141],"$K$-phase":[143],"($K\\geq":[145],"2$)":[146],"choosing":[148],"$(K-1)$":[149],"after":[151],"found.":[154],"Changing":[155],"$K$":[156],"does":[160],"not":[161],"require":[162],"recomputed.":[166],"Experimental":[167],"results":[168],"show":[169],"that":[170],"performs":[174],"better":[175],"than":[176],"many":[177],"standard":[178],"two-phase":[179],"multiphase":[181],"methods":[183],"very":[185],"general":[186],"images,":[187],"including":[188],"antimass,":[189],"tubular,":[190],"magnetic":[191],"resonance":[192],"imaging,":[193],"low-light":[195],"images.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}