{"id":"https://openalex.org/W1984996808","doi":"https://doi.org/10.1109/wocn.2013.6616235","title":"Image denoising using wavelet transform method","display_name":"Image denoising using wavelet transform method","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W1984996808","doi":"https://doi.org/10.1109/wocn.2013.6616235","mag":"1984996808"},"language":"en","primary_location":{"id":"doi:10.1109/wocn.2013.6616235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wocn.2013.6616235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 Tenth International Conference on Wireless and Optical Communications Networks (WOCN)","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/A5104061094","display_name":"Vikas Gupta","orcid":null},"institutions":[{"id":"https://openalex.org/I196622127","display_name":"Rajiv Gandhi Technical University","ror":"https://ror.org/03xmje391","country_code":"IN","type":"education","lineage":["https://openalex.org/I196622127"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vikas Gupta","raw_affiliation_strings":["H.O.D. of ECE Department, TIT, Rajiv Gandhi Technical University, Bhopal, Madhya Pradesh, India","ECE Dept., Rajiv Gandhi Tech. Univ., Bhopal, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"H.O.D. of ECE Department, TIT, Rajiv Gandhi Technical University, Bhopal, Madhya Pradesh, India","institution_ids":["https://openalex.org/I196622127"]},{"raw_affiliation_string":"ECE Dept., Rajiv Gandhi Tech. Univ., Bhopal, India","institution_ids":["https://openalex.org/I196622127"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108410224","display_name":"Rajesh Mahle","orcid":null},"institutions":[{"id":"https://openalex.org/I196622127","display_name":"Rajiv Gandhi Technical University","ror":"https://ror.org/03xmje391","country_code":"IN","type":"education","lineage":["https://openalex.org/I196622127"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajesh Mahle","raw_affiliation_strings":["ECE Department, TIT, Rajiv Gandhi Technical University, Bhopal, Madhya Pradesh, India","ECE Dept., Rajiv Gandhi Tech. Univ., Bhopal, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECE Department, TIT, Rajiv Gandhi Technical University, Bhopal, Madhya Pradesh, India","institution_ids":["https://openalex.org/I196622127"]},{"raw_affiliation_string":"ECE Dept., Rajiv Gandhi Tech. Univ., Bhopal, India","institution_ids":["https://openalex.org/I196622127"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055126853","display_name":"Raviprakash S. Shriwas","orcid":null},"institutions":[{"id":"https://openalex.org/I196622127","display_name":"Rajiv Gandhi Technical University","ror":"https://ror.org/03xmje391","country_code":"IN","type":"education","lineage":["https://openalex.org/I196622127"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Raviprakash S Shriwas","raw_affiliation_strings":["ECE Department, TIT, Rajiv Gandhi Technical University, Bhopal, Madhya Pradesh, India","ECE Dept., Rajiv Gandhi Tech. Univ., Bhopal, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECE Department, TIT, Rajiv Gandhi Technical University, Bhopal, Madhya Pradesh, India","institution_ids":["https://openalex.org/I196622127"]},{"raw_affiliation_string":"ECE Dept., Rajiv Gandhi Tech. Univ., Bhopal, India","institution_ids":["https://openalex.org/I196622127"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2101,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.88993727,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"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":0.9998999834060669,"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":0.9986000061035156,"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":0.9693999886512756,"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/noise-reduction","display_name":"Noise reduction","score":0.7047970294952393},{"id":"https://openalex.org/keywords/step-detection","display_name":"Step detection","score":0.7028446197509766},{"id":"https://openalex.org/keywords/video-denoising","display_name":"Video denoising","score":0.693089485168457},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6443278193473816},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6400381922721863},{"id":"https://openalex.org/keywords/non-local-means","display_name":"Non-local means","score":0.6316666007041931},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6054797172546387},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5729192495346069},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5613202452659607},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5178985595703125},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.49061813950538635},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.4637869596481323},{"id":"https://openalex.org/keywords/peak-signal-to-noise-ratio","display_name":"Peak signal-to-noise ratio","score":0.4601905643939972},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39717668294906616},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3290499448776245},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.25697946548461914},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.15662908554077148},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.09112104773521423}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.7047970294952393},{"id":"https://openalex.org/C293773","wikidata":"https://www.wikidata.org/wiki/Q7608015","display_name":"Step detection","level":3,"score":0.7028446197509766},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.693089485168457},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6443278193473816},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6400381922721863},{"id":"https://openalex.org/C101453961","wikidata":"https://www.wikidata.org/wiki/Q7048948","display_name":"Non-local means","level":4,"score":0.6316666007041931},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6054797172546387},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5729192495346069},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5613202452659607},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5178985595703125},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.49061813950538635},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.4637869596481323},{"id":"https://openalex.org/C154579607","wikidata":"https://www.wikidata.org/wiki/Q3373850","display_name":"Peak signal-to-noise ratio","level":3,"score":0.4601905643939972},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39717668294906616},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3290499448776245},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25697946548461914},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.15662908554077148},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.09112104773521423},{"id":"https://openalex.org/C23431618","wikidata":"https://www.wikidata.org/wiki/Q1404672","display_name":"Multiview Video Coding","level":4,"score":0.0},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wocn.2013.6616235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wocn.2013.6616235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 Tenth International Conference on Wireless and Optical Communications Networks (WOCN)","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":11,"referenced_works":["https://openalex.org/W1971613160","https://openalex.org/W1993357058","https://openalex.org/W1993934841","https://openalex.org/W1997461753","https://openalex.org/W2002474737","https://openalex.org/W2046447936","https://openalex.org/W2098115093","https://openalex.org/W2132984323","https://openalex.org/W2170393132","https://openalex.org/W2325606010","https://openalex.org/W3104992617"],"related_works":["https://openalex.org/W2348643679","https://openalex.org/W233850645","https://openalex.org/W2372414973","https://openalex.org/W2082304850","https://openalex.org/W2367199645","https://openalex.org/W2903172302","https://openalex.org/W4213271663","https://openalex.org/W2078677256","https://openalex.org/W1699622673","https://openalex.org/W2606645259"],"abstract_inverted_index":{"Removing":[0],"noise":[1,26,135,185],"from":[2,27,191],"the":[3,40,88,98,107,111,147,175,181,184,192],"original":[4,28],"signal":[5,160],"is":[6,82,172],"still":[7,83],"a":[8,33,84,103,144],"challenging":[9],"job":[10],"for":[11,79,159],"researchers.":[12],"There":[13],"have":[14],"been":[15],"several":[16,53],"numbers":[17],"of":[18,35,42,50,66,69,90,106,117,146,149,177],"published":[19],"algorithms":[20,154],"and":[21,60,93,101,124,126,137,166],"each":[22],"target":[23],"to":[24,134,173],"remove":[25],"signal.":[29],"This":[30],"paper":[31],"presents":[32],"result":[34,176],"some":[36],"significant":[37],"work":[38],"in":[39,129,180],"area":[41],"image":[43,72,80,164,167],"denoising":[44,49,73,81,150],"it":[45],"means":[46],"we":[47,63,96],"explore":[48],"images":[51],"using":[52],"thresholding":[54],"methods":[55],"such":[56,119,162],"as":[57,120,143,163],"SureShrink,":[58],"VisuShrink":[59],"BayesShrink.":[61],"Here":[62,95,110],"put":[64],"results":[65,112],"different":[67],"approaches":[68],"wavelet":[70,178],"based":[71,113],"methods.":[74],"To":[75],"find":[76],"best":[77],"method":[78],"valid":[85],"challenge":[86],"at":[87],"crossing":[89],"functional":[91],"analysis":[92],"statistics.":[94],"extend":[97],"existing":[99],"technique":[100],"providing":[102],"comprehensive":[104],"evaluation":[105],"proposed":[108],"method.":[109],"on":[114],"various":[115],"types":[116],"noise,":[118],"Gaussian,":[121],"Poisson's,":[122],"Salt":[123],"Pepper,":[125],"Speckle":[127],"performed":[128],"this":[130],"paper.":[131],"SNR":[132],"(signal":[133],"ratio)":[136],"mean":[138],"square":[139],"error":[140],"(MSE)":[141],"are":[142,155],"measure":[145],"quality":[148],"was":[151],"preferred.":[152],"Wavelet":[153],"very":[156],"useful":[157],"tool":[158],"processing":[161],"compression":[165],"denoising.":[168],"The":[169],"main":[170],"aim":[171],"show":[174],"coefficients":[179],"new":[182],"basis,":[183],"can":[186],"be":[187],"minimize":[188],"or":[189],"removed":[190],"data.":[193]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":18},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
