{"id":"https://openalex.org/W4205575639","doi":"https://doi.org/10.1109/ispacs51563.2021.9651001","title":"Image Contrast Enhancement with High Dynamic Range using Singlescale Retinex","display_name":"Image Contrast Enhancement with High Dynamic Range using Singlescale Retinex","publication_year":2021,"publication_date":"2021-11-16","ids":{"openalex":"https://openalex.org/W4205575639","doi":"https://doi.org/10.1109/ispacs51563.2021.9651001"},"language":"en","primary_location":{"id":"doi:10.1109/ispacs51563.2021.9651001","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispacs51563.2021.9651001","pdf_url":null,"source":{"id":"https://openalex.org/S4363605678","display_name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","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/A5100764559","display_name":"Hideaki Tanaka","orcid":"https://orcid.org/0000-0001-9964-3652"},"institutions":[{"id":"https://openalex.org/I185088104","display_name":"Tokyo City University","ror":"https://ror.org/04dt6bw53","country_code":"JP","type":"education","lineage":["https://openalex.org/I185088104"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hideaki Tanaka","raw_affiliation_strings":["Tokyo City Unversity, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo City Unversity, Tokyo, Japan","institution_ids":["https://openalex.org/I185088104"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053910121","display_name":"Akira Taguchi","orcid":"https://orcid.org/0000-0003-2620-1487"},"institutions":[{"id":"https://openalex.org/I185088104","display_name":"Tokyo City University","ror":"https://ror.org/04dt6bw53","country_code":"JP","type":"education","lineage":["https://openalex.org/I185088104"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Taguchi","raw_affiliation_strings":["Tokyo City University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo City University, Tokyo, Japan","institution_ids":["https://openalex.org/I185088104"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100764559"],"corresponding_institution_ids":["https://openalex.org/I185088104"],"apc_list":null,"apc_paid":null,"fwci":0.196,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58914171,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9986000061035156,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9986000061035156,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9860000014305115,"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/color-constancy","display_name":"Color constancy","score":0.8256057500839233},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.8198912143707275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6956652402877808},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6535604000091553},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.610859751701355},{"id":"https://openalex.org/keywords/image-enhancement","display_name":"Image enhancement","score":0.5613141059875488},{"id":"https://openalex.org/keywords/dynamic-range","display_name":"Dynamic range","score":0.5564859509468079},{"id":"https://openalex.org/keywords/contrast-enhancement","display_name":"Contrast enhancement","score":0.5284647345542908},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5187811851501465},{"id":"https://openalex.org/keywords/high-dynamic-range","display_name":"High dynamic range","score":0.5143964886665344},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5138083100318909},{"id":"https://openalex.org/keywords/image-contrast","display_name":"Image contrast","score":0.4680730104446411},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32923758029937744},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.14910992980003357}],"concepts":[{"id":"https://openalex.org/C187888035","wikidata":"https://www.wikidata.org/wiki/Q2563885","display_name":"Color constancy","level":3,"score":0.8256057500839233},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.8198912143707275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6956652402877808},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6535604000091553},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.610859751701355},{"id":"https://openalex.org/C3017601658","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image enhancement","level":3,"score":0.5613141059875488},{"id":"https://openalex.org/C87133666","wikidata":"https://www.wikidata.org/wiki/Q1161699","display_name":"Dynamic range","level":2,"score":0.5564859509468079},{"id":"https://openalex.org/C3018181011","wikidata":"https://www.wikidata.org/wiki/Q6849688","display_name":"Contrast enhancement","level":3,"score":0.5284647345542908},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5187811851501465},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.5143964886665344},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5138083100318909},{"id":"https://openalex.org/C3018302497","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Image contrast","level":2,"score":0.4680730104446411},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32923758029937744},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.14910992980003357},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ispacs51563.2021.9651001","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispacs51563.2021.9651001","pdf_url":null,"source":{"id":"https://openalex.org/S4363605678","display_name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W2121900453","https://openalex.org/W3023411394"],"related_works":["https://openalex.org/W1847360884","https://openalex.org/W3031737451","https://openalex.org/W2890853391","https://openalex.org/W3009327912","https://openalex.org/W2390497845","https://openalex.org/W3211387963","https://openalex.org/W2739324174","https://openalex.org/W2393933564","https://openalex.org/W4402511303","https://openalex.org/W2376933780"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3],"contrast":[4,11,24,76],"enhancement":[5,25],"method":[6,26,82],"for":[7,27],"images":[8],"with":[9],"low":[10],"areas":[12],"due":[13],"to":[14,35,43,69,86],"uneven":[15],"illumination.":[16],"The":[17,80],"multi-scale":[18],"retinex":[19,66],"(MSR)":[20],"is":[21,40,59,77,91],"an":[22],"excellent":[23],"such":[28],"images.":[29],"However,":[30],"MSR":[31],"contains":[32],"many":[33],"parameters":[34,46,85,95],"be":[36,87,97],"determined":[37,98],"and":[38,74,112],"it":[39,90],"not":[41],"easy":[42],"determine":[44],"those":[45],"properly.":[47],"In":[48],"the":[49,52,56,63,70,75,94,101,104,108],"proposed":[50,81],"method,":[51],"dynamic":[53],"range":[54],"of":[55,107],"entire":[57],"image":[58,110],"maintained":[60],"by":[61,99],"adding":[62],"single":[64],"scale":[65],"(SSR)":[67],"result":[68],"scaled":[71],"original":[72],"image,":[73],"effectively":[78],"improved.":[79],"has":[83],"few":[84],"determined.":[88],"Therefore,":[89],"clarified":[92],"that":[93],"can":[96],"specifying":[100],"difference":[102],"between":[103],"average":[105],"values":[106],"whole":[109],"before":[111],"after":[113],"enhancement.":[114]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
