{"id":"https://openalex.org/W2293349539","doi":"https://doi.org/10.1109/icip.2015.7351031","title":"Dark image enhancement based onpairwise target contrast and multi-scale detail boosting","display_name":"Dark image enhancement based onpairwise target contrast and multi-scale detail boosting","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2293349539","doi":"https://doi.org/10.1109/icip.2015.7351031","mag":"2293349539"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2015.7351031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","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/A5101753787","display_name":"Youngbae Kim","orcid":"https://orcid.org/0000-0003-0542-7559"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngbae Kim","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047570965","display_name":"Yeong Jun Koh","orcid":"https://orcid.org/0000-0003-1805-2960"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yeong Jun Koh","raw_affiliation_strings":["Korea University, Seongbuk-gu, Seoul, KR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea University, Seongbuk-gu, Seoul, KR","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003657120","display_name":"Chulwoo Lee","orcid":"https://orcid.org/0000-0002-3837-7992"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chulwoo Lee","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090263674","display_name":"Sehoon Kim","orcid":"https://orcid.org/0000-0001-7652-8803"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sehoon Kim","raw_affiliation_strings":["Digital Media & Communications R&D Center, Samsung Electronics, Suwon, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Digital Media & Communications R&D Center, Samsung Electronics, Suwon, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063748248","display_name":"Chang\u2010Su Kim","orcid":"https://orcid.org/0000-0002-4276-1831"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chang-Su Kim","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.15377043,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1404","last_page":"1408"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":1.0,"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":1.0,"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":0.9970999956130981,"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/T11666","display_name":"Color Science and Applications","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.824394702911377},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.7890951633453369},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7292487025260925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6715706586837769},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6195521950721741},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.6088159680366516},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5012857913970947},{"id":"https://openalex.org/keywords/visibility","display_name":"Visibility","score":0.4655832350254059},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46297428011894226},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.4153408706188202},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38492006063461304},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.09172806143760681}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.824394702911377},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7890951633453369},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7292487025260925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6715706586837769},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6195521950721741},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.6088159680366516},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5012857913970947},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.4655832350254059},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46297428011894226},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.4153408706188202},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38492006063461304},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.09172806143760681},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2015.7351031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1984939790","https://openalex.org/W1987444808","https://openalex.org/W1995875735","https://openalex.org/W2011260964","https://openalex.org/W2011954520","https://openalex.org/W2054814429","https://openalex.org/W2061501622","https://openalex.org/W2113745526","https://openalex.org/W2123293628","https://openalex.org/W2125732958","https://openalex.org/W2170288257","https://openalex.org/W2242047952","https://openalex.org/W2997077506","https://openalex.org/W6646425552","https://openalex.org/W6677048112"],"related_works":["https://openalex.org/W2392812199","https://openalex.org/W4200176076","https://openalex.org/W598185802","https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W1549363203","https://openalex.org/W4231274751","https://openalex.org/W2355516524","https://openalex.org/W1691631808","https://openalex.org/W1586320973"],"abstract_inverted_index":{"A":[0],"dark":[1,113],"image":[2],"enhancement":[3],"algorithm":[4,106],"based":[5],"on":[6],"the":[7,12,24,35,41,45,50,68,72,77,83,96,104,108],"pairwise":[8,25,51],"target":[9,26,52],"contrast":[10,27,109],"and":[11,81,110],"multi-scale":[13,90],"detail":[14],"boosting":[15],"is":[16],"proposed":[17,105],"in":[18,44,59,95],"this":[19],"work.":[20],"We":[21],"first":[22],"compute":[23],"between":[28],"a":[29,64,89],"pair":[30],"of":[31,40,57,112],"pixels,":[32],"which":[33],"represents":[34],"desired":[36],"gray":[37],"level":[38],"difference":[39],"two":[42],"pixels":[43,58],"output":[46],"image.":[47,84,99],"By":[48,70],"aggregating":[49],"contrasts":[53],"for":[54,67],"all":[55],"pairs":[56],"an":[60],"image,":[61],"we":[62,75,87],"formulate":[63],"cost":[65,73],"function":[66,80],"enhancement.":[69],"minimizing":[71],"function,":[74],"obtain":[76],"optimal":[78],"transformation":[79],"enhance":[82],"In":[85],"addition,":[86],"propose":[88],"approach":[91],"to":[92],"boost":[93],"details":[94],"globally":[97],"enhanced":[98],"Experimental":[100],"results":[101],"show":[102],"that":[103],"enhances":[107],"visibility":[111],"images":[114],"more":[115],"effectively":[116],"than":[117],"conventional":[118],"algorithms.":[119]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
