{"id":"https://openalex.org/W2052857611","doi":"https://doi.org/10.1109/icce-berlin.2014.7034260","title":"Texture preserving noise reduction for ultra high ISO images","display_name":"Texture preserving noise reduction for ultra high ISO images","publication_year":2014,"publication_date":"2014-09-01","ids":{"openalex":"https://openalex.org/W2052857611","doi":"https://doi.org/10.1109/icce-berlin.2014.7034260","mag":"2052857611"},"language":"en","primary_location":{"id":"doi:10.1109/icce-berlin.2014.7034260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-berlin.2014.7034260","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Fourth International Conference on Consumer Electronics Berlin (ICCE-Berlin)","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/A5005718078","display_name":"Hee Chul Han","orcid":"https://orcid.org/0000-0003-0374-8690"},"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":true,"raw_author_name":"Heechul Han","raw_affiliation_strings":["Digital Media & Communication R&D Center, Samsung Electronics, Suwon City, South Korea"],"affiliations":[{"raw_affiliation_string":"Digital Media & Communication R&D Center, Samsung Electronics, Suwon City, South Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111760360","display_name":"Hyun seok Hong","orcid":null},"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":"Hyun seok Hong","raw_affiliation_strings":["Digital Media & Communication R&D Center, Samsung Electronics, Suwon City, South Korea"],"affiliations":[{"raw_affiliation_string":"Digital Media & Communication R&D Center, Samsung Electronics, Suwon City, South Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088474756","display_name":"Seungki Cho","orcid":null},"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":"Seungki Cho","raw_affiliation_strings":["Digital Media & Communication R&D Center, Samsung Electronics, Suwon City, South Korea"],"affiliations":[{"raw_affiliation_string":"Digital Media & Communication R&D Center, Samsung Electronics, Suwon City, South Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104165871","display_name":"Jingu Jeong","orcid":null},"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":"Jingu Jeong","raw_affiliation_strings":["Digital Media & Communication R&D Center, Samsung Electronics, Suwon City, South Korea"],"affiliations":[{"raw_affiliation_string":"Digital Media & Communication R&D Center, Samsung Electronics, Suwon City, South Korea","institution_ids":["https://openalex.org/I2250650973"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5005718078"],"corresponding_institution_ids":["https://openalex.org/I2250650973"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.11786327,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"2","issue":null,"first_page":"415","last_page":"419"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9993000030517578,"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":0.9991000294685364,"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/gaussian-noise","display_name":"Gaussian noise","score":0.6956827640533447},{"id":"https://openalex.org/keywords/impulse-noise","display_name":"Impulse noise","score":0.6545092463493347},{"id":"https://openalex.org/keywords/value-noise","display_name":"Value noise","score":0.6467986106872559},{"id":"https://openalex.org/keywords/gradient-noise","display_name":"Gradient noise","score":0.6204473376274109},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6166263222694397},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6152995824813843},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.580115556716919},{"id":"https://openalex.org/keywords/image-noise","display_name":"Image noise","score":0.5570380687713623},{"id":"https://openalex.org/keywords/salt-and-pepper-noise","display_name":"Salt-and-pepper noise","score":0.5532627701759338},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.530095636844635},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.49761465191841125},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.48808157444000244},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4712762236595154},{"id":"https://openalex.org/keywords/median-filter","display_name":"Median filter","score":0.47073519229888916},{"id":"https://openalex.org/keywords/dark-frame-subtraction","display_name":"Dark-frame subtraction","score":0.4404976963996887},{"id":"https://openalex.org/keywords/colors-of-noise","display_name":"Colors of noise","score":0.41427576541900635},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3768806457519531},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.27427831292152405},{"id":"https://openalex.org/keywords/noise-floor","display_name":"Noise floor","score":0.23471808433532715},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21504119038581848},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.1468881368637085}],"concepts":[{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6956827640533447},{"id":"https://openalex.org/C127372701","wikidata":"https://www.wikidata.org/wiki/Q16979398","display_name":"Impulse noise","level":3,"score":0.6545092463493347},{"id":"https://openalex.org/C182163834","wikidata":"https://www.wikidata.org/wiki/Q2926529","display_name":"Value noise","level":5,"score":0.6467986106872559},{"id":"https://openalex.org/C200378446","wikidata":"https://www.wikidata.org/wiki/Q4147391","display_name":"Gradient noise","level":5,"score":0.6204473376274109},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6166263222694397},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6152995824813843},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.580115556716919},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.5570380687713623},{"id":"https://openalex.org/C113660513","wikidata":"https://www.wikidata.org/wiki/Q849379","display_name":"Salt-and-pepper noise","level":5,"score":0.5532627701759338},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.530095636844635},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.49761465191841125},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.48808157444000244},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4712762236595154},{"id":"https://openalex.org/C55352655","wikidata":"https://www.wikidata.org/wiki/Q304247","display_name":"Median filter","level":4,"score":0.47073519229888916},{"id":"https://openalex.org/C1160358","wikidata":"https://www.wikidata.org/wiki/Q861103","display_name":"Dark-frame subtraction","level":5,"score":0.4404976963996887},{"id":"https://openalex.org/C114996537","wikidata":"https://www.wikidata.org/wiki/Q4854529","display_name":"Colors of noise","level":3,"score":0.41427576541900635},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3768806457519531},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27427831292152405},{"id":"https://openalex.org/C187612029","wikidata":"https://www.wikidata.org/wiki/Q17083130","display_name":"Noise floor","level":4,"score":0.23471808433532715},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21504119038581848},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.1468881368637085}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce-berlin.2014.7034260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-berlin.2014.7034260","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Fourth International Conference on Consumer Electronics Berlin (ICCE-Berlin)","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":3,"referenced_works":["https://openalex.org/W2027091505","https://openalex.org/W2105134732","https://openalex.org/W2339768163"],"related_works":["https://openalex.org/W2306622391","https://openalex.org/W2980586888","https://openalex.org/W4379184580","https://openalex.org/W2618419521","https://openalex.org/W2810312662","https://openalex.org/W2186246304","https://openalex.org/W3140076208","https://openalex.org/W2011016717","https://openalex.org/W2182876982","https://openalex.org/W2189335616"],"abstract_inverted_index":{"We":[0,16,106],"present":[1],"a":[2,7,21,36,74,108,137,147],"novel":[3],"method":[4],"to":[5,42,123,136],"reduce":[6],"sparkle":[8],"and":[9,24,47,61,141,150],"impulse":[10],"noise":[11,45,51,70,79,91,101,116,138,144],"of":[12,100,126],"high":[13],"ISO":[14,60],"images.":[15],"employ":[17],"diverse":[18],"approach":[19],"for":[20,64,112,145],"intensity(Y)":[22],"image":[23,135,140,149],"two":[25],"Color":[26],"images":[27],"(CB,CR)":[28],"separately.":[29],"For":[30],"the":[31,65,83,94,114,120,124,127],"intensity":[32,69],"image,":[33],"we":[34,130],"propose":[35],"frequency":[37,75],"cut":[38,77],"based":[39,78],"texture":[40,48],"analysis":[41,52],"distinguish":[43],"between":[44],"patch":[46,85],"patch.":[49,92],"A":[50],"calibration":[53],"is":[54,71],"proposed":[55,107],"depending":[56],"on":[57],"exposure":[58],"time,":[59],"sensor":[62],"size":[63,99],"parameter":[66],"extraction.":[67],"The":[68],"removed":[72],"by":[73,118],"magnitude":[76,89],"reduction":[80],"assuming":[81],"that":[82],"pattern":[84,153],"has":[86],"much":[87],"higher":[88],"than":[90],"However":[93],"color":[95,115],"parts":[96],"produce":[97],"big":[98],"mass":[102,117],"after":[103],"CFA":[104],"interpolation.":[105],"coincidental":[109],"smoothing":[110],"filter":[111],"removing":[113],"applying":[119],"Gaussian":[121,143],"function":[122],"strength":[125],"color.":[128],"Finally":[129],"blend":[131],"an":[132],"input":[133],"noisy":[134],"reduced":[139],"add":[142],"making":[146],"natural":[148],"reducing":[151],"some":[152],"loss.":[154]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}