{"id":"https://openalex.org/W2136312067","doi":"https://doi.org/10.1109/iccv.2009.5459239","title":"Image segmentation with simultaneous illumination and reflectance estimation: An energy minimization approach","display_name":"Image segmentation with simultaneous illumination and reflectance estimation: An energy minimization approach","publication_year":2009,"publication_date":"2009-09-01","ids":{"openalex":"https://openalex.org/W2136312067","doi":"https://doi.org/10.1109/iccv.2009.5459239","mag":"2136312067"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2009.5459239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision","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/A5100701327","display_name":"Chunming Li","orcid":"https://orcid.org/0000-0002-4159-7048"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chunming Li","raw_affiliation_strings":["Vanderbilt University Institute of Imaging Science, Nashville, TN, USA","Vanderbilt University Institute of Imaging Science, Nashville, TN 37232 USA"],"affiliations":[{"raw_affiliation_string":"Vanderbilt University Institute of Imaging Science, Nashville, TN, USA","institution_ids":["https://openalex.org/I200719446"]},{"raw_affiliation_string":"Vanderbilt University Institute of Imaging Science, Nashville, TN 37232 USA","institution_ids":["https://openalex.org/I200719446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074370589","display_name":"Li Fang","orcid":"https://orcid.org/0009-0009-5342-7036"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]},{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Li","raw_affiliation_strings":["Department of Mathematics, East China Jiao Tong University, Shanghai, China","Department of Mathematics , East China Normal University, Shanghai 200062, China)"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, East China Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Department of Mathematics , East China Normal University, Shanghai 200062, China)","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045327320","display_name":"Chiu\u2010Yen Kao","orcid":"https://orcid.org/0000-0003-3082-4943"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chiu-Yen Kao","raw_affiliation_strings":["Department of Mathematics, Ohio State Uinversity, Columbus, OH, USA","Department of Mathematics, The Ohio State University, Columbus 43210, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Ohio State Uinversity, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"Department of Mathematics, The Ohio State University, Columbus 43210, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102008317","display_name":"Chenyang Xu","orcid":"https://orcid.org/0000-0002-3212-8450"},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenyang Xu","raw_affiliation_strings":["Siemens AG Corporate Research and Development, Princeton, NJ, USA","Siemens Corporate Research, Princeton NJ 08540, USA"],"affiliations":[{"raw_affiliation_string":"Siemens AG Corporate Research and Development, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]},{"raw_affiliation_string":"Siemens Corporate Research, Princeton NJ 08540, USA","institution_ids":["https://openalex.org/I4210137693"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100701327"],"corresponding_institution_ids":["https://openalex.org/I200719446"],"apc_list":null,"apc_paid":null,"fwci":2.6244,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.91026821,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"702","last_page":"708"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9984999895095825,"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":0.9984999895095825,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.998199999332428,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9980999827384949,"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":0.7453992962837219},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7223235368728638},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.6400913596153259},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6214251518249512},{"id":"https://openalex.org/keywords/energy-minimization","display_name":"Energy minimization","score":0.6192632913589478},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5972863435745239},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5895476937294006},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5628533363342285},{"id":"https://openalex.org/keywords/reflectivity","display_name":"Reflectivity","score":0.5100139379501343},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.47851359844207764},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.47284653782844543},{"id":"https://openalex.org/keywords/energy-functional","display_name":"Energy functional","score":0.4381425380706787},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4217071831226349},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35670945048332214},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31044304370880127},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.27562984824180603},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11245569586753845}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7453992962837219},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7223235368728638},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.6400913596153259},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6214251518249512},{"id":"https://openalex.org/C14961307","wikidata":"https://www.wikidata.org/wiki/Q5377176","display_name":"Energy minimization","level":2,"score":0.6192632913589478},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5972863435745239},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5895476937294006},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5628533363342285},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.5100139379501343},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47851359844207764},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.47284653782844543},{"id":"https://openalex.org/C191640071","wikidata":"https://www.wikidata.org/wiki/Q5377056","display_name":"Energy functional","level":2,"score":0.4381425380706787},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4217071831226349},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35670945048332214},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31044304370880127},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.27562984824180603},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11245569586753845},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iccv.2009.5459239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.299.1010","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.299.1010","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.engr.uconn.edu/~cmli/paper/Li_ICCV09.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8500000238418579,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W39428922","https://openalex.org/W1990675808","https://openalex.org/W1994794884","https://openalex.org/W2005089986","https://openalex.org/W2016422699","https://openalex.org/W2038495454","https://openalex.org/W2063690897","https://openalex.org/W2098152234","https://openalex.org/W2114487471","https://openalex.org/W2116040950","https://openalex.org/W2136748901","https://openalex.org/W2154423567","https://openalex.org/W2159152281","https://openalex.org/W2164847484","https://openalex.org/W2165734775","https://openalex.org/W6601593943"],"related_works":["https://openalex.org/W1518796764","https://openalex.org/W2118841422","https://openalex.org/W347294048","https://openalex.org/W2226908759","https://openalex.org/W1899667806","https://openalex.org/W2061881449","https://openalex.org/W1981231660","https://openalex.org/W1483822002","https://openalex.org/W4281970230","https://openalex.org/W2891476794"],"abstract_inverted_index":{"Spatial":[0],"intensity":[1],"variations":[2,155],"caused":[3,152],"by":[4,153],"illumination":[5,33,52,71,119,137],"changes":[6],"have":[7],"been":[8],"a":[9,23,55],"challenge":[10],"for":[11,26],"image":[12,27,49,103,126],"segmentation":[13,28,104],"and":[14,34,54,79,120],"many":[15],"other":[16],"computer":[17],"vision":[18],"tasks.":[19],"This":[20,90],"paper":[21],"presents":[22],"novel":[24],"method":[25,39,143],"with":[29,50,149,159],"simultaneous":[30],"estimation":[31],"of":[32,45,69,76,84,96,111,115,123,133,169],"reflectance":[35,56,82,121],"images.":[36,61],"The":[37,118],"proposed":[38,142],"is":[40,92,106,144],"based":[41],"on":[42],"the":[43,73,77,80,85,88,101,109,112,116,124,131,141,160,166],"composition":[44],"an":[46,51,64,70],"observed":[47,125],"scene":[48],"component":[53],"component,":[57],"known":[58],"as":[59,130],"intrinsic":[60],"We":[62],"define":[63],"energy":[65,91,134],"functional":[66],"in":[67,87,94,108,156],"terms":[68],"image,":[72],"membership":[74,113],"functions":[75,114],"regions,":[78],"corresponding":[81],"constants":[83],"regions":[86],"scene.":[89],"convex":[93],"each":[95],"its":[97],"variables.":[98],"By":[99],"minimizing":[100],"energy,":[102],"result":[105,132],"obtained":[107],"form":[110],"regions.":[117],"components":[122],"are":[127],"estimated":[128],"simultaneously":[129],"minimization.":[135],"With":[136],"taken":[138],"into":[139],"account,":[140],"able":[145],"to":[146],"segment":[147],"images":[148],"non-uniform":[150],"intensities":[151],"spatial":[154],"illumination.":[157],"Comparisons":[158],"state-of-the-art":[161],"piecewise":[162],"smooth":[163],"model":[164],"demonstrate":[165],"superior":[167],"performance":[168],"our":[170],"method.":[171]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
