{"id":"https://openalex.org/W2601359817","doi":"https://doi.org/10.1109/tpami.2017.2689765","title":"A Hybrid Shared-Memory Parallel Max-Tree Algorithm for Extreme Dynamic-Range Images","display_name":"A Hybrid Shared-Memory Parallel Max-Tree Algorithm for Extreme Dynamic-Range Images","publication_year":2017,"publication_date":"2017-03-31","ids":{"openalex":"https://openalex.org/W2601359817","doi":"https://doi.org/10.1109/tpami.2017.2689765","mag":"2601359817","pmid":"https://pubmed.ncbi.nlm.nih.gov/28371773"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2017.2689765","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2017.2689765","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://research.rug.nl/en/publications/057e9149-5a0c-433b-be4e-50940407baa7","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091433746","display_name":"Ugo Moschini","orcid":"https://orcid.org/0000-0002-8006-6039"},"institutions":[{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Ugo Moschini","raw_affiliation_strings":["Johann Bernoulli Institute, University of Groningen, Groningen, The Netherlands"],"raw_orcid":"https://orcid.org/0000-0002-8006-6039","affiliations":[{"raw_affiliation_string":"Johann Bernoulli Institute, University of Groningen, Groningen, The Netherlands","institution_ids":["https://openalex.org/I169381384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062120246","display_name":"Arnold Meijster","orcid":null},"institutions":[{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Arnold Meijster","raw_affiliation_strings":["Johann Bernoulli Institute, University of Groningen, Groningen, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johann Bernoulli Institute, University of Groningen, Groningen, The Netherlands","institution_ids":["https://openalex.org/I169381384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015726919","display_name":"Michael H. F. Wilkinson","orcid":"https://orcid.org/0000-0001-6258-1128"},"institutions":[{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Michael H. F. Wilkinson","raw_affiliation_strings":["Johann Bernoulli Institute, University of Groningen, Groningen, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johann Bernoulli Institute, University of Groningen, Groningen, The Netherlands","institution_ids":["https://openalex.org/I169381384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5091433746"],"corresponding_institution_ids":["https://openalex.org/I169381384"],"apc_list":null,"apc_paid":null,"fwci":0.9244,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.83586568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"40","issue":"3","first_page":"513","last_page":"526"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9955999851226807,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9955999851226807,"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":0.982200026512146,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9789000153541565,"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/computer-science","display_name":"Computer science","score":0.7157520055770874},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5015411376953125},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4976973831653595},{"id":"https://openalex.org/keywords/parallel-algorithm","display_name":"Parallel algorithm","score":0.4518156349658966},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4369139075279236},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42241692543029785},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3572827875614166},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.3555026054382324},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1564631164073944}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7157520055770874},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5015411376953125},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4976973831653595},{"id":"https://openalex.org/C120373497","wikidata":"https://www.wikidata.org/wiki/Q1087987","display_name":"Parallel algorithm","level":2,"score":0.4518156349658966},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4369139075279236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42241692543029785},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3572827875614166},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3555026054382324},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1564631164073944},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/tpami.2017.2689765","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2017.2689765","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:28371773","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28371773","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:pure.rug.nl:openaire/057e9149-5a0c-433b-be4e-50940407baa7","is_oa":true,"landing_page_url":"https://research.rug.nl/en/publications/057e9149-5a0c-433b-be4e-50940407baa7","pdf_url":null,"source":{"id":"https://openalex.org/S4306400420","display_name":"University of Groningen research database (University of Groningen / Centre for Information Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I169381384","host_organization_name":"University of Groningen","host_organization_lineage":["https://openalex.org/I169381384"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Moschini, U, Meijster, A & Wilkinson, M 2018, 'A Hybrid Shared-Memory Parallel Max-Tree Algorithm for Extreme Dynamic-Range Images', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 3, pp. 513-526. https://doi.org/10.1109/TPAMI.2017.2689765","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.rug.nl:publications/057e9149-5a0c-433b-be4e-50940407baa7","is_oa":true,"landing_page_url":"https://hdl.handle.net/11370/057e9149-5a0c-433b-be4e-50940407baa7","pdf_url":"https://pure.rug.nl/ws/files/55482697/A_Hybrid_Shared_Memory_Parallel_Max_Tree_Algorithm.pdf","source":{"id":"https://openalex.org/S4306400420","display_name":"University of Groningen research database (University of Groningen / Centre for Information Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I169381384","host_organization_name":"University of Groningen","host_organization_lineage":["https://openalex.org/I169381384"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Moschini, U, Meijster, A & Wilkinson, M 2018, 'A Hybrid Shared-Memory Parallel Max-Tree Algorithm for Extreme Dynamic-Range Images', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 3, pp. 513-526. https://doi.org/10.1109/TPAMI.2017.2689765","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:zenodo.org:3526425","is_oa":true,"landing_page_url":"https://zenodo.org/record/3526425","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:pure.rug.nl:openaire/057e9149-5a0c-433b-be4e-50940407baa7","is_oa":true,"landing_page_url":"https://research.rug.nl/en/publications/057e9149-5a0c-433b-be4e-50940407baa7","pdf_url":null,"source":{"id":"https://openalex.org/S4306400420","display_name":"University of Groningen research database (University of Groningen / Centre for Information Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I169381384","host_organization_name":"University of Groningen","host_organization_lineage":["https://openalex.org/I169381384"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Moschini, U, Meijster, A & Wilkinson, M 2018, 'A Hybrid Shared-Memory Parallel Max-Tree Algorithm for Extreme Dynamic-Range Images', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 3, pp. 513-526. https://doi.org/10.1109/TPAMI.2017.2689765","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5102235669","display_name":null,"funder_award_id":"612.001.110","funder_id":"https://openalex.org/F4320321800","funder_display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek"}],"funders":[{"id":"https://openalex.org/F4320321800","display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","ror":"https://ror.org/04jsz6e67"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W11165332","https://openalex.org/W73629738","https://openalex.org/W1975610128","https://openalex.org/W1986022261","https://openalex.org/W1988585795","https://openalex.org/W2012605804","https://openalex.org/W2028089458","https://openalex.org/W2036073865","https://openalex.org/W2047076586","https://openalex.org/W2074688378","https://openalex.org/W2079512692","https://openalex.org/W2088682428","https://openalex.org/W2099096599","https://openalex.org/W2111311839","https://openalex.org/W2112720808","https://openalex.org/W2118197877","https://openalex.org/W2129217551","https://openalex.org/W2134188917","https://openalex.org/W2146842130","https://openalex.org/W2149301680","https://openalex.org/W2154174545","https://openalex.org/W2155780766","https://openalex.org/W2159498975","https://openalex.org/W2161711000","https://openalex.org/W2171884975","https://openalex.org/W2181914484","https://openalex.org/W2258720767","https://openalex.org/W2345551181","https://openalex.org/W2487963376","https://openalex.org/W2489008212","https://openalex.org/W2586047224","https://openalex.org/W2946046356","https://openalex.org/W6676631768","https://openalex.org/W6682766343","https://openalex.org/W6723108451","https://openalex.org/W6733471522"],"related_works":["https://openalex.org/W2115140794","https://openalex.org/W2041120224","https://openalex.org/W4312275919","https://openalex.org/W2067902980","https://openalex.org/W2070865675","https://openalex.org/W1970073092","https://openalex.org/W1657646819","https://openalex.org/W338671845","https://openalex.org/W2054653010","https://openalex.org/W2070426974"],"abstract_inverted_index":{"Max-trees,":[0],"or":[1,29],"component":[2],"trees,":[3],"are":[4,152],"graph":[5],"structures":[6],"that":[7,52],"represent":[8],"the":[9,53,77,95,118,124,127,131,138,156],"connected":[10],"components":[11],"of":[12,45,80,90,94,126,137],"an":[13,135],"image":[14,96],"in":[15,99,110],"a":[16,73,87,91,102,111],"hierarchical":[17],"way.":[18],"Nowadays,":[19],"many":[20],"application":[21],"fields":[22],"rely":[23],"on":[24,141,165],"images":[25,44,146],"with":[26,60],"high-dynamic":[27],"range":[28],"floating":[30],"point":[31],"values.":[32],"Efficient":[33],"sequential":[34,158],"algorithms":[35,56],"exist":[36],"to":[37,115,122,164],"build":[38],"trees":[39],"and":[40,82,121,143,147,160],"compute":[41,116],"attributes":[42],"for":[43],"any":[46],"bit":[47,63],"depth.":[48],"However,":[49],"we":[50],"show":[51],"current":[54],"parallel":[55,74,100,112],"perform":[57],"poorly":[58],"already":[59],"integers":[61],"at":[62],"depths":[64],"higher":[65],"than":[66,155],"16":[67],"bits":[68],"per":[69],"pixel.":[70],"We":[71,133],"propose":[72],"method":[75],"combining":[76],"two":[78],"worlds":[79],"flooding":[81,103],"merging":[83,125],"max-tree":[84,89,120],"algorithms.":[85],"First,":[86],"pilot":[88],"quantized":[92],"version":[93],"is":[97,108],"built":[98],"using":[101],"method.":[104],"Later,":[105],"this":[106],"structure":[107],"used":[109],"leaf-to-root":[113],"approach":[114],"efficiently":[117],"final":[119],"drive":[123],"sub-trees":[128],"computed":[129],"by":[130],"threads.":[132,167],"present":[134],"analysis":[136],"performance":[139],"both":[140],"simulated":[142],"actual":[144],"2D":[145],"3D":[148],"volumes.":[149],"Execution":[150],"times":[151],"about":[153],"better":[154],"fastest":[157],"algorithm":[159],"speed-up":[161],"goes":[162],"up":[163],"64":[166]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}