{"id":"https://openalex.org/W2015296957","doi":"https://doi.org/10.1117/12.2083147","title":"Enhanced correction methods for high density hot pixel defects in digital imagers","display_name":"Enhanced correction methods for high density hot pixel defects in digital imagers","publication_year":2015,"publication_date":"2015-03-13","ids":{"openalex":"https://openalex.org/W2015296957","doi":"https://doi.org/10.1117/12.2083147","mag":"2015296957"},"language":"en","primary_location":{"id":"doi:10.1117/12.2083147","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2083147","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},"type":"conference-paper","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/A5061097022","display_name":"Glenn H. Chapman","orcid":"https://orcid.org/0000-0002-2486-2954"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Glenn H. Chapman","raw_affiliation_strings":["Simon Fraser Univ. (Canada)","Simon Fraser University CANADA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser Univ. (Canada)","institution_ids":["https://openalex.org/I18014758"]},{"raw_affiliation_string":"Simon Fraser University CANADA","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068982210","display_name":"Rahul Thomas","orcid":"https://orcid.org/0009-0004-4755-5174"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Rahul Thomas","raw_affiliation_strings":["Simon Fraser Univ. (Canada)","Simon Fraser University CANADA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser Univ. (Canada)","institution_ids":["https://openalex.org/I18014758"]},{"raw_affiliation_string":"Simon Fraser University CANADA","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080720196","display_name":"Rohit Thomas","orcid":null},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Rohit Thomas","raw_affiliation_strings":["Simon Fraser Univ. (Canada)","Simon Fraser University CANADA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser Univ. (Canada)","institution_ids":["https://openalex.org/I18014758"]},{"raw_affiliation_string":"Simon Fraser University CANADA","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023125411","display_name":"Zahava Koren","orcid":null},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zahava Koren","raw_affiliation_strings":["Univ. of Massachusetts Amherst (United States)","University of Massachusetts, Amherst, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Massachusetts Amherst (United States)","institution_ids":["https://openalex.org/I24603500"]},{"raw_affiliation_string":"University of Massachusetts, Amherst, United States","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055210733","display_name":"Israel Koren","orcid":"https://orcid.org/0000-0003-2741-7108"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Israel Koren","raw_affiliation_strings":["Univ. of Massachusetts Amherst (United States)","University of Massachusetts, Amherst, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Massachusetts Amherst (United States)","institution_ids":["https://openalex.org/I24603500"]},{"raw_affiliation_string":"University of Massachusetts, Amherst, United States","institution_ids":["https://openalex.org/I24603500"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.11626835,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"9403","issue":null,"first_page":"94030T","last_page":"94030T"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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":0.9993000030517578,"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":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.9125247001647949},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6548582911491394},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.6463984847068787},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6369092464447021},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.629494845867157},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.4744081199169159},{"id":"https://openalex.org/keywords/digital-image","display_name":"Digital image","score":0.4425341486930847},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.39171063899993896},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.358824223279953},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2273888885974884}],"concepts":[{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.9125247001647949},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6548582911491394},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.6463984847068787},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6369092464447021},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.629494845867157},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.4744081199169159},{"id":"https://openalex.org/C42781572","wikidata":"https://www.wikidata.org/wiki/Q1250322","display_name":"Digital image","level":4,"score":0.4425341486930847},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39171063899993896},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.358824223279953},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2273888885974884},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2083147","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2083147","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2027654975","https://openalex.org/W2031457674","https://openalex.org/W2043988312","https://openalex.org/W2110449873","https://openalex.org/W2113100884","https://openalex.org/W2122230135","https://openalex.org/W2156916124","https://openalex.org/W2158150403","https://openalex.org/W3142913228","https://openalex.org/W6657224702","https://openalex.org/W6658299272","https://openalex.org/W6677163916","https://openalex.org/W6677901311","https://openalex.org/W6683301835"],"related_works":["https://openalex.org/W1998512593","https://openalex.org/W3101578490","https://openalex.org/W4213477128","https://openalex.org/W4287300272","https://openalex.org/W3155045749","https://openalex.org/W3134797699","https://openalex.org/W4313427965","https://openalex.org/W2117577511","https://openalex.org/W1497877549","https://openalex.org/W2392126150"],"abstract_inverted_index":{"Our":[0],"previous":[1],"research":[2],"has":[3],"found":[4],"that":[5,67,121,129,180],"the":[6,35,96,99,107,138,148,174,178,194,198],"main":[7],"defects":[8,46],"in":[9,49],"digital":[10],"cameras":[11,50],"are":[12,85],"\u201cHot":[13],"Pixels\u201d":[14],"which":[15],"increase":[16],"at":[17],"a":[18,31,63,69,117,134,152,167,183,190],"nearly":[19],"constant":[20],"temporal":[21],"rate.":[22],"Defect":[23],"rates":[24],"have":[25,105,115],"been":[26],"shown":[27],"to":[28,43],"grow":[29],"as":[30],"power":[32],"law":[33],"of":[34,45,72,95,109,155,177,193],"pixel":[36,80,101,179,185,199],"size":[37,200],"and":[38,78,93,114,201],"ISO,":[39,90],"potentially":[40],"causing":[41],"hundreds":[42],"thousands":[44],"per":[47],"year":[48],"with":[51,133],"&lt;2":[52],"micron":[53],"pixels,":[54],"thus":[55],"making":[56],"image":[57,132],"correction":[58,65,119,149],"crucial.":[59],"This":[60,187],"paper":[61],"discusses":[62],"novel":[64,168],"method":[66,171,188],"uses":[68],"weighted":[70,153],"combination":[71,154],"two":[73],"terms":[74],"-":[75],"traditional":[76],"interpolation":[77,140],"hot":[79,100,110,184],"parameters":[81,102],"correction.":[82],"The":[83],"weights":[84],"based":[86,196],"on":[87,197],"defect":[88],"severity,":[89],"exposure":[91],"time":[92],"complexity":[94],"image.":[97],"For":[98],"component,":[103],"we":[104,165],"studied":[106],"behavior":[108,124],"pixels":[111],"under":[112],"illumination":[113],"created":[116],"new":[118],"model":[120],"takes":[122],"this":[123],"into":[125],"account.":[126],"We":[127],"show":[128],"for":[130,144,172],"an":[131],"slowly":[135],"changing":[136],"background,":[137],"classic":[139],"performs":[141],"well.":[142],"However,":[143],"more":[145],"complex":[146],"scenes,":[147],"improves":[150],"when":[151],"both":[156],"components":[157],"is":[158],"used.":[159],"To":[160],"test":[161],"our":[162],"algorithm\u2019s":[163],"accuracy,":[164],"devised":[166],"laboratory":[169],"experimental":[170],"extracting":[173],"true":[175],"value":[176],"currently":[181],"experiences":[182],"defect.":[186],"involves":[189],"simple":[191],"translation":[192],"imager":[195],"other":[202],"optical":[203],"distances.":[204]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
