{"id":"https://openalex.org/W2093964406","doi":"https://doi.org/10.1109/mlsp.2015.7324356","title":"A Naive Bayes approach to improve histogram matching quality","display_name":"A Naive Bayes approach to improve histogram matching quality","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2093964406","doi":"https://doi.org/10.1109/mlsp.2015.7324356","mag":"2093964406"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2015.7324356","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2015.7324356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5003579185","display_name":"Fahd Bouzaraa","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Fahd Bouzaraa","raw_affiliation_strings":["Technical University of Munich"],"affiliations":[{"raw_affiliation_string":"Technical University of Munich","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021221556","display_name":"Onay Urfal\u0131o\u01e7lu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210160618","display_name":"Huawei Technologies (United Kingdom)","ror":"https://ror.org/056gzgs71","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210160618"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Onay Urfalioglu","raw_affiliation_strings":["Huawei Technologies Co. Ltd","Huawei Technologies, Co., Ltd"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co. Ltd","institution_ids":["https://openalex.org/I4210160618"]},{"raw_affiliation_string":"Huawei Technologies, Co., Ltd","institution_ids":["https://openalex.org/I4210160618"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5003579185"],"corresponding_institution_ids":["https://openalex.org/I62916508"],"apc_list":null,"apc_paid":null,"fwci":0.1841,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.57845633,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994999766349792,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994999766349792,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9988999962806702,"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":0.9987000226974487,"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":0.7998969554901123},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6647454500198364},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6371979117393494},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6076304316520691},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5558724999427795},{"id":"https://openalex.org/keywords/histogram-matching","display_name":"Histogram matching","score":0.5543948411941528},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5075424909591675},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.491669237613678},{"id":"https://openalex.org/keywords/color-histogram","display_name":"Color histogram","score":0.4884580671787262},{"id":"https://openalex.org/keywords/image-histogram","display_name":"Image histogram","score":0.4403547942638397},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.43442708253860474},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.42697060108184814},{"id":"https://openalex.org/keywords/color-image","display_name":"Color image","score":0.36980679631233215},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3527568280696869},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26114800572395325},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15340012311935425}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7998969554901123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6647454500198364},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6371979117393494},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6076304316520691},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5558724999427795},{"id":"https://openalex.org/C127449775","wikidata":"https://www.wikidata.org/wiki/Q3785871","display_name":"Histogram matching","level":4,"score":0.5543948411941528},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5075424909591675},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.491669237613678},{"id":"https://openalex.org/C12043971","wikidata":"https://www.wikidata.org/wiki/Q2636542","display_name":"Color histogram","level":5,"score":0.4884580671787262},{"id":"https://openalex.org/C62725073","wikidata":"https://www.wikidata.org/wiki/Q1771663","display_name":"Image histogram","level":5,"score":0.4403547942638397},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.43442708253860474},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.42697060108184814},{"id":"https://openalex.org/C142616399","wikidata":"https://www.wikidata.org/wiki/Q5148604","display_name":"Color image","level":4,"score":0.36980679631233215},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3527568280696869},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26114800572395325},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15340012311935425}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp.2015.7324356","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2015.7324356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP)","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":10,"referenced_works":["https://openalex.org/W2008790887","https://openalex.org/W2097073572","https://openalex.org/W2102584639","https://openalex.org/W2104974755","https://openalex.org/W2141966243","https://openalex.org/W2145023731","https://openalex.org/W2293879958","https://openalex.org/W3029544904","https://openalex.org/W4234282793","https://openalex.org/W4244003036"],"related_works":["https://openalex.org/W2066185872","https://openalex.org/W2065866067","https://openalex.org/W2375849557","https://openalex.org/W1979012573","https://openalex.org/W2152100107","https://openalex.org/W4239902432","https://openalex.org/W1994838069","https://openalex.org/W2109325523","https://openalex.org/W2110241600","https://openalex.org/W2943995207"],"abstract_inverted_index":{"Histogram":[0],"Matching":[1],"(HM)":[2],"is":[3,25,52,93,133,219],"a":[4,13,19,90,94,111,175,220],"well":[5,194],"known":[6],"technique":[7],"for":[8,96,115],"matching":[9],"the":[10,44,49,61,81,86,117,127,142,148,160,200],"colors":[11],"of":[12,18,80,119,126,137,144,185,210],"source":[14,82,161],"image":[15,87,104,150],"to":[16,36,56,159,181],"those":[17],"reference":[20,128,149],"image.":[21,129,162],"A":[22],"major":[23],"application":[24],"High":[26],"Dynamic":[27],"Range":[28],"Imaging,":[29],"where":[30],"images":[31,45,62,122],"with":[32,213],"different":[33],"exposures":[34],"have":[35],"be":[37,65],"color":[38,50,71,100],"matched.":[39],"HM":[40,74],"works":[41],"best":[42],"when":[43],"are":[46,206],"aligned":[47],"and":[48,98,102,169],"difference":[51,156],"small.":[53],"However,":[54],"due":[55],"camera":[57],"or":[58],"object":[59],"motion,":[60],"may":[63],"not":[64],"aligned,":[66],"which":[67,84,153,218],"can":[68],"result":[69],"in":[70,157],"artifacts.":[72],"Furthermore,":[73],"typically":[75],"involves":[76],"brightening":[77],"dark":[78],"regions":[79],"image,":[83],"increases":[85],"noise.":[88,105],"As":[89],"result,":[91],"there":[92],"need":[95],"detecting":[97],"correcting":[99],"artifacts":[101],"increased":[103],"In":[106,179],"this":[107],"paper":[108],"we":[109,167],"present":[110],"novel":[112],"post-processing":[113],"method":[114,132,212],"improving":[116],"quality":[118],"histogram":[120],"matched":[121],"using":[123],"statistical":[124],"properties":[125],"The":[130],"proposed":[131],"based":[134,216],"on":[135,164,208],"ensembles":[136,146],"neighboring":[138],"pixels.":[139],"We":[140],"learn":[141],"statistics":[143],"such":[145],"within":[147],"(target":[151],"image),":[152],"exhibits":[154],"content":[155],"comparison":[158],"Based":[163],"these":[165],"statistics,":[166],"detect":[168],"reconstruct":[170],"faulty":[171],"intensities,":[172],"by":[173],"following":[174],"naive":[176],"Bayes":[177],"approach.":[178],"addition":[180],"its":[182],"relative":[183],"easiness":[184],"implementation,":[186],"experimental":[187],"results":[188,205],"show":[189],"considerable":[190],"subjective":[191],"(visual)":[192],"as":[193,195],"objective":[196],"(PSNR)":[197],"improvements":[198],"over":[199],"original":[201],"HM.":[202],"Moreover,":[203],"promising":[204],"obtained":[207],"comparisons":[209],"our":[211],"Non-Local-Means":[214],"denoising":[215,222],"post-processing,":[217],"state-of-the-art":[221],"method.":[223]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}