{"id":"https://openalex.org/W2575028755","doi":"https://doi.org/10.2352/issn.2470-1173.2016.18.dpmi-248","title":"Local Linear Approximation for Camera Image Processing Pipelines","display_name":"Local Linear Approximation for Camera Image Processing Pipelines","publication_year":2016,"publication_date":"2016-02-14","ids":{"openalex":"https://openalex.org/W2575028755","doi":"https://doi.org/10.2352/issn.2470-1173.2016.18.dpmi-248","mag":"2575028755"},"language":"en","primary_location":{"id":"doi:10.2352/issn.2470-1173.2016.18.dpmi-248","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2016.18.dpmi-248","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-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/A5101765752","display_name":"Haomiao Jiang","orcid":"https://orcid.org/0000-0002-0214-6869"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haomiao Jiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066843175","display_name":"Qiyuan Tian","orcid":"https://orcid.org/0000-0002-8350-5295"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiyuan Tian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013356576","display_name":"Joyce Farrell","orcid":"https://orcid.org/0000-0003-3919-1978"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joyce Farrell","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5074011246","display_name":"Brian A. Wandell","orcid":"https://orcid.org/0000-0002-2974-1836"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brian Wandell","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.14342207,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"28","issue":"18","first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9997000098228455,"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/T11105","display_name":"Advanced Image Processing Techniques","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"}}],"keywords":[{"id":"https://openalex.org/keywords/demosaicing","display_name":"Demosaicing","score":0.7964763641357422},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7502671480178833},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6394434571266174},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5953473448753357},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5900840759277344},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5791386961936951},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.5771539807319641},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.5109137892723083},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4860387444496155},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4464977979660034},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.304512083530426},{"id":"https://openalex.org/keywords/color-image","display_name":"Color image","score":0.2766016125679016},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09063941240310669}],"concepts":[{"id":"https://openalex.org/C27624317","wikidata":"https://www.wikidata.org/wiki/Q263499","display_name":"Demosaicing","level":5,"score":0.7964763641357422},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7502671480178833},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6394434571266174},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5953473448753357},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5900840759277344},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5791386961936951},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.5771539807319641},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.5109137892723083},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4860387444496155},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4464977979660034},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.304512083530426},{"id":"https://openalex.org/C142616399","wikidata":"https://www.wikidata.org/wiki/Q5148604","display_name":"Color image","level":4,"score":0.2766016125679016},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09063941240310669},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2352/issn.2470-1173.2016.18.dpmi-248","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2016.18.dpmi-248","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1946953458","https://openalex.org/W1963892077","https://openalex.org/W1990381576","https://openalex.org/W2021347102","https://openalex.org/W2071398741","https://openalex.org/W2550544110"],"related_works":["https://openalex.org/W2105489289","https://openalex.org/W2976757711","https://openalex.org/W4380433113","https://openalex.org/W4386072068","https://openalex.org/W252339960","https://openalex.org/W2571738250","https://openalex.org/W2390529043","https://openalex.org/W2118150509","https://openalex.org/W3140715649","https://openalex.org/W1991529554"],"abstract_inverted_index":{"Modern":[0],"digital":[1],"cameras":[2],"include":[3],"an":[4],"image":[5,70],"processing":[6,71,129],"pipeline":[7,23,107],"that":[8,47,149],"converts":[9],"raw":[10],"sensor":[11],"data":[12,28],"to":[13,37,51,173],"a":[14,39,76,132,154],"rendered":[15,82,103,111],"RGB":[16],"image.":[17],"Several":[18],"key":[19],"steps":[20],"in":[21,67],"the":[22,57,62,65,68,91,94,98,101,105,109,113,125,143,150],"operate":[24],"on":[25,162],"spatially":[26],"localized":[27],"(demosaicking,":[29],"noise":[30],"reduction,":[31],"color":[32],"conversion).":[33],"We":[34,73],"show":[35],"how":[36],"derive":[38,75],"collection":[40],"of":[41,64,78,93,136,142,153,157],"local,":[42,114,118],"adaptive":[43,58],"linear":[44,59,115,119,146,158],"filters":[45],"(kernels)":[46],"can":[48,167],"be":[49,168],"applied":[50],"each":[52],"pixel":[53],"and":[54,120,127,145,166],"its":[55],"neighborhood;":[56],"calculation":[60],"approximates":[61],"performance":[63],"modules":[66],"conventional":[69],"pipeline.":[72],"also":[74],"set":[77],"kernels":[79,123,159],"from":[80],"images":[81,102,110],"by":[83,96,104,112],"expert":[84,128],"photographers.":[85],"In":[86],"both":[87],"cases,":[88],"we":[89],"evaluate":[90],"accuracy":[92],"approximation":[95],"calculating":[97],"difference":[99],"between":[100],"camera":[106,126],"with":[108,131,171],"approximation.":[116],"The":[117],"learned":[121],"(L3)":[122],"approximate":[124],"pipelines":[130],"mean":[133],"S-CIELAB":[134],"error":[135],"ΔE":[137],"<":[138],"2.":[139],"A":[140],"value":[141],"local":[144],"architecture":[147],"is":[148],"parallel":[151],"application":[152],"large":[155],"number":[156],"works":[160],"well":[161],"modern":[163],"hardware":[164],"configurations":[165],"implemented":[169],"efficiently":[170],"respect":[172],"power.":[174]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}