{"id":"https://openalex.org/W2295952922","doi":"https://doi.org/10.1109/icip.2015.7351714","title":"Pseudo four-channel image denoising for noisy CFA raw data","display_name":"Pseudo four-channel image denoising for noisy CFA raw data","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2295952922","doi":"https://doi.org/10.1109/icip.2015.7351714","mag":"2295952922"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2015.7351714","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351714","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":"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/A5075695222","display_name":"Hiroki Akiyama","orcid":"https://orcid.org/0000-0003-1765-8813"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroki Akiyama","raw_affiliation_strings":["Tokyo Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040292386","display_name":"Masayuki Tanaka","orcid":"https://orcid.org/0000-0002-5756-1904"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masayuki Tanaka","raw_affiliation_strings":["Tokyo Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024453747","display_name":"Masatoshi Okutomi","orcid":"https://orcid.org/0000-0001-5787-0742"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masatoshi Okutomi","raw_affiliation_strings":["Tokyo Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I114531698"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4778","last_page":"4782"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998999834060669,"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":0.9998999834060669,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9994000196456909,"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6906006336212158},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.6640690565109253},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6304574012756348},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.586394727230072},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5732426643371582},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5113479495048523},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4720419645309448},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4710552394390106},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4402419924736023},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41552406549453735},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09518858790397644}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6906006336212158},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.6640690565109253},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6304574012756348},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.586394727230072},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5732426643371582},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5113479495048523},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4720419645309448},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4710552394390106},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4402419924736023},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41552406549453735},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09518858790397644},{"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:10.1109/icip.2015.7351714","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351714","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W96697480","https://openalex.org/W1912194039","https://openalex.org/W1969210895","https://openalex.org/W1971114016","https://openalex.org/W1999046526","https://openalex.org/W2003884262","https://openalex.org/W2028140315","https://openalex.org/W2035192779","https://openalex.org/W2053779250","https://openalex.org/W2060994093","https://openalex.org/W2086375115","https://openalex.org/W2129381747","https://openalex.org/W2152178471","https://openalex.org/W2155311268","https://openalex.org/W2294473561","https://openalex.org/W2536599074","https://openalex.org/W6659304788"],"related_works":["https://openalex.org/W2005185696","https://openalex.org/W2161229648","https://openalex.org/W2235753890","https://openalex.org/W2993674027","https://openalex.org/W2130228941","https://openalex.org/W2092957489","https://openalex.org/W2366116130","https://openalex.org/W2314419244","https://openalex.org/W2132132164","https://openalex.org/W2483420468"],"abstract_inverted_index":{"Most":[0],"demosaicking":[1,23],"algorithms":[2],"only":[3],"focus":[4],"on":[5,30,70],"handling":[6],"noise-free":[7],"CFA":[8,14,40,50,97,105,118],"raw":[9,15,41,51,98,106,119],"data.":[10,99,120],"In":[11,45],"practice,":[12],"the":[13,31,34,46,49,64,71,89,103,111,116,125],"data":[16,42,52,66,91,107],"are":[17,67],"corrupted":[18],"by":[19,60],"noise,":[20],"which":[21],"degrades":[22],"performance.":[24],"Full-color":[25],"image":[26,59,79,113],"quality":[27],"strongly":[28],"depends":[29],"performance":[32],"of":[33],"demosaicking.":[35],"Here,":[36],"we":[37],"propose":[38],"a":[39,56],"denoising":[43,80],"algorithm.":[44],"proposed":[47,126],"algorithm,":[48],"is":[53,82,92],"converted":[54],"to":[55,84,94],"pseudo":[57],"four-channel":[58,65],"rearranging":[61],"pixels.":[62],"Then,":[63],"transformed":[68,86],"based":[69],"principal":[72],"component":[73],"analysis":[74],"(PCA).":[75],"Existing":[76],"high-performance":[77],"gray":[78],"algorithm":[81,127],"applied":[83],"each":[85],"image.":[87],"Finally,":[88],"denoised":[90,96,104],"rearranged":[93],"obtain":[95],"We":[100],"evaluate":[101],"both":[102],"as":[108,110],"well":[109],"full-color":[112],"reconstructed":[114],"with":[115],"noisy":[117],"Experimental":[121],"comparisons":[122],"demonstrate":[123],"that":[124],"outperforms":[128],"existing":[129],"state-of-the-art":[130],"algorithms.":[131]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
