{"id":"https://openalex.org/W3110841027","doi":"https://doi.org/10.1109/smc42975.2020.9283042","title":"Colour Image Denoising using Curvelets and Scale Dependent Shrinkage","display_name":"Colour Image Denoising using Curvelets and Scale Dependent Shrinkage","publication_year":2020,"publication_date":"2020-10-11","ids":{"openalex":"https://openalex.org/W3110841027","doi":"https://doi.org/10.1109/smc42975.2020.9283042","mag":"3110841027"},"language":"en","primary_location":{"id":"doi:10.1109/smc42975.2020.9283042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc42975.2020.9283042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5061337663","display_name":"Oussama Kadri","orcid":"https://orcid.org/0000-0002-2573-7485"},"institutions":[{"id":"https://openalex.org/I206961696","display_name":"University of Biskra","ror":"https://ror.org/05fr5y859","country_code":"DZ","type":"education","lineage":["https://openalex.org/I206961696"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Oussama Kadri","raw_affiliation_strings":["Mohammed Khider University, Biskra, Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mohammed Khider University, Biskra, Algeria","institution_ids":["https://openalex.org/I206961696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110815453","display_name":"Zine-Eddine Baarir","orcid":null},"institutions":[{"id":"https://openalex.org/I206961696","display_name":"University of Biskra","ror":"https://ror.org/05fr5y859","country_code":"DZ","type":"education","lineage":["https://openalex.org/I206961696"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Zine-Eddine Baarir","raw_affiliation_strings":["Mohammed Khider University, Biskra, Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mohammed Khider University, Biskra, Algeria","institution_ids":["https://openalex.org/I206961696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105462955","display_name":"Gerald Schaefer","orcid":"https://orcid.org/0000-0003-1292-7674"},"institutions":[{"id":"https://openalex.org/I143804889","display_name":"Loughborough University","ror":"https://ror.org/04vg4w365","country_code":"GB","type":"education","lineage":["https://openalex.org/I143804889"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gerald Schaefer","raw_affiliation_strings":["Loughborough University, Loughborough, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Loughborough University, Loughborough, U.K","institution_ids":["https://openalex.org/I143804889"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059308026","display_name":"Iakov Korovin","orcid":"https://orcid.org/0000-0001-5192-8835"},"institutions":[{"id":"https://openalex.org/I137534880","display_name":"Southern Federal University","ror":"https://ror.org/01tv9ph92","country_code":"RU","type":"education","lineage":["https://openalex.org/I137534880"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Iakov Korovin","raw_affiliation_strings":["Southern Federal University, Taganrog, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern Federal University, Taganrog, Russia","institution_ids":["https://openalex.org/I137534880"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14549065,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"2072","last_page":"2077"},"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":0.9984999895095825,"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":0.9941999912261963,"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/curvelet","display_name":"Curvelet","score":0.8592442274093628},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8224080801010132},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.7801110744476318},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6953699588775635},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.561471700668335},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5382930636405945},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5354825258255005},{"id":"https://openalex.org/keywords/ycbcr","display_name":"YCbCr","score":0.5136820673942566},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.4947449862957001},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.44867560267448425},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4274730384349823},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.39438772201538086},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38371190428733826},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37937211990356445},{"id":"https://openalex.org/keywords/color-image","display_name":"Color image","score":0.2992069721221924},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.21623468399047852},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.15161296725273132}],"concepts":[{"id":"https://openalex.org/C131720326","wikidata":"https://www.wikidata.org/wiki/Q5196075","display_name":"Curvelet","level":4,"score":0.8592442274093628},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8224080801010132},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.7801110744476318},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6953699588775635},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.561471700668335},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5382930636405945},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5354825258255005},{"id":"https://openalex.org/C2779407163","wikidata":"https://www.wikidata.org/wiki/Q1189998","display_name":"YCbCr","level":5,"score":0.5136820673942566},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.4947449862957001},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.44867560267448425},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4274730384349823},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.39438772201538086},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38371190428733826},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37937211990356445},{"id":"https://openalex.org/C142616399","wikidata":"https://www.wikidata.org/wiki/Q5148604","display_name":"Color image","level":4,"score":0.2992069721221924},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.21623468399047852},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.15161296725273132}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc42975.2020.9283042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc42975.2020.9283042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/W1485280399","https://openalex.org/W2047710600","https://openalex.org/W2069912449","https://openalex.org/W2098070646","https://openalex.org/W2115528090","https://openalex.org/W2132680427","https://openalex.org/W2133665775","https://openalex.org/W2138057336","https://openalex.org/W2169467627","https://openalex.org/W2324971623","https://openalex.org/W2406034201","https://openalex.org/W2546664592","https://openalex.org/W2913349789","https://openalex.org/W2943117671","https://openalex.org/W2963315679","https://openalex.org/W6674582754","https://openalex.org/W6701249984"],"related_works":["https://openalex.org/W138221400","https://openalex.org/W4317671434","https://openalex.org/W2922872563","https://openalex.org/W2549418288","https://openalex.org/W2739092184","https://openalex.org/W2740804836","https://openalex.org/W4321317645","https://openalex.org/W2939643258","https://openalex.org/W3107671540","https://openalex.org/W2744754738"],"abstract_inverted_index":{"With":[0],"the":[1,19,64,80,84,99,122],"widespread":[2],"use":[3],"of":[4,21,24,36,98,115],"image":[5,76,93],"processing":[6,54],"and":[7,31,46,118,121,139],"computer":[8],"vision":[9],"applications,":[10],"effective":[11],"denoising":[12],"methods":[13,133],"are":[14,39,47],"highly":[15],"sought":[16],"after,":[17],"prompting":[18],"development":[20],"a":[22],"variety":[23],"algorithms":[25],"under":[26],"different":[27],"assumptions":[28],"on":[29,102],"noise":[30,110],"signal":[32],"properties.":[33],"However,":[34],"most":[35],"these":[37],"techniques":[38],"developed":[40],"to":[41,50,74,89,128,131],"deal":[42],"with":[43],"grayscale":[44,72],"images,":[45,73],"typically":[48],"extended":[49],"colour":[51,75,87,103],"images":[52,104],"by":[53,78,106],"each":[55],"RGB":[56],"channel":[57],"separately.":[58],"In":[59],"this":[60],"paper,":[61],"we":[62],"extend":[63],"curvelet":[65,135],"power":[66],"shrinkage":[67],"algorithm,":[68],"introduced":[69],"previously":[70],"for":[71],"denoising,":[77],"applying":[79],"proposed":[81,100],"method":[82,127],"in":[83,113],"luminance/opponent-colour":[85],"YCbCr":[86],"space":[88],"take":[90],"into":[91],"consideration":[92],"inter-channel":[94],"dependencies.":[95],"The":[96],"performance":[97],"algorithm":[101],"corrupted":[105],"additive":[107],"white":[108],"Gaussian":[109],"is":[111],"evaluated":[112],"terms":[114],"both":[116],"objective":[117],"subjective":[119],"measures,":[120],"obtained":[123],"results":[124],"show":[125],"our":[126],"be":[129],"competitive":[130],"other":[132],"including":[134],"domain":[136],"hard":[137],"thresholding":[138],"MSt-SVD.":[140]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}