{"id":"https://openalex.org/W18046889","doi":null,"title":"A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way","display_name":"A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way","publication_year":2008,"publication_date":"2008-12-26","ids":{"openalex":"https://openalex.org/W18046889","mag":"18046889"},"language":"en","primary_location":{"id":"mag:18046889","doi":null,"is_oa":false,"landing_page_url":"https://dl.acm.org/citation.cfm?id=1525499","pdf_url":null,"source":{"id":"https://openalex.org/S4306462761","display_name":"Academic Press eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319955","host_organization_name":"Academic Press","host_organization_lineage":["https://openalex.org/P4310319955","https://openalex.org/P4310320990"],"host_organization_lineage_names":["Academic Press","Elsevier BV"],"type":"ebook platform"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Academic Press eBooks","raw_type":null},"volume":null,"type":"book","is_traditional":true,"indexed_in":[],"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/A5025963782","display_name":"Stphane Mallat","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Stphane Mallat","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5025963782"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":15.0212,"has_fulltext":false,"cited_by_count":950,"citation_normalized_percentile":{"value":1.0,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.7339000105857849,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.7339000105857849,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11210","display_name":"Mathematical Analysis and Transform Methods","score":0.22269999980926514,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.03779999911785126,"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/sparse-representation","display_name":"sparse representation","score":0.890999972820282},{"id":"https://openalex.org/keywords/wavelets","display_name":"wavelets","score":0.8029999732971191},{"id":"https://openalex.org/keywords/time-frequency-transforms","display_name":"time-frequency transforms","score":0.7599999904632568},{"id":"https://openalex.org/keywords/orthogonal-basis","display_name":"orthogonal bases","score":0.7089999914169312},{"id":"https://openalex.org/keywords/signal-compression","display_name":"signal compression","score":0.7820000052452087},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"noise reduction","score":0.9580000042915344},{"id":"https://openalex.org/keywords/inverse-problems","display_name":"inverse problems","score":0.925000011920929},{"id":"https://openalex.org/keywords/redundant-dictionaries","display_name":"redundant dictionaries","score":0.9259999990463257},{"id":"https://openalex.org/keywords/super-resolution","display_name":"super-resolution","score":0.9269999861717224},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"compressed sensing","score":0.9900000095367432},{"id":"https://openalex.org/keywords/source-separation","display_name":"source separation","score":0.8450000286102295},{"id":"https://openalex.org/keywords/curvelets","display_name":"curvelets","score":0.9829999804496765},{"id":"https://openalex.org/keywords/jpeg-2000","display_name":"JPEG2000","score":0.7979999780654907},{"id":"https://openalex.org/keywords/image-compression","display_name":"image compression","score":0.7889999747276306},{"id":"https://openalex.org/keywords/audio-denoising","display_name":"audio denoising","score":0.7639999985694885}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6065425872802734},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.594560444355011},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5822722911834717},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5405588746070862},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.49962496757507324},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.49641138315200806},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3833608329296112},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3640541732311249},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3616296052932739},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35752853751182556},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.34129002690315247},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1712796986103058},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.11112961173057556}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:18046889","doi":null,"is_oa":false,"landing_page_url":"https://dl.acm.org/citation.cfm?id=1525499","pdf_url":null,"source":{"id":"https://openalex.org/S4306462761","display_name":"Academic Press eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319955","host_organization_name":"Academic Press","host_organization_lineage":["https://openalex.org/P4310319955","https://openalex.org/P4310320990"],"host_organization_lineage_names":["Academic Press","Elsevier BV"],"type":"ebook platform"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Academic Press eBooks","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W1933984380","https://openalex.org/W2400783999"],"related_works":["https://openalex.org/W228380312","https://openalex.org/W1591116419","https://openalex.org/W2493239084","https://openalex.org/W7015465049","https://openalex.org/W2277416294","https://openalex.org/W3142914389","https://openalex.org/W4254546220","https://openalex.org/W2579586009","https://openalex.org/W2342756229","https://openalex.org/W1574645113"],"abstract_inverted_index":{"Mallat's":[0],"book":[1,35,59,289],"is":[2,11,85,99,197,230],"the":[3,12,17,38,48,51,62,72,115,209,249,284,288,313],"undisputed":[4],"reference":[5],"in":[6,20,54,104,128,145,151,211,232,292,306],"this":[7,33,146],"field":[8],"-":[9,25],"it":[10],"only":[13],"one":[14],"that":[15],"covers":[16],"essential":[18],"material":[19],"such":[21,213],"breadth":[22],"and":[23,42,68,71,87,94,108,123,137,140,156,164,177,184,203,219,226,259,262,266,299,301],"depth.":[24],"Laurent":[26],"Demanet,":[27],"Stanford":[28],"UniversityThe":[29],"new":[30],"edition":[31],"of":[32,44,74,83,114,189,252,269,279,312],"classic":[34],"gives":[36],"all":[37,283],"major":[39],"concepts,":[40],"techniques":[41],"applications":[43,118,316],"sparse":[45,102],"representation,":[46],"reflecting":[47],"key":[49],"role":[50],"subject":[52],"plays":[53],"today's":[55],"signal":[56,90,120,149,318],"processing.":[57],"The":[58,80,192],"clearly":[60],"presents":[61],"standard":[63],"representations":[64,103,150],"with":[65,77,117,162,170,181,315],"Fourier,":[66],"wavelet":[67],"time-frequency":[69],"transforms,":[70],"construction":[73],"orthogonal":[75],"bases":[76],"fast":[78],"algorithms.":[79],"central":[81],"concept":[82],"sparsity":[84],"explained":[86],"applied":[88],"to":[89,101,119,207,242,296,317],"compression,":[91,220],"noise":[92],"reduction,":[93],"inverse":[95],"problems,":[96],"while":[97],"coverage":[98],"given":[100],"redundant":[105],"dictionaries,":[106],"super-resolution":[107,155],"compressive":[109],"sensing":[110],"applications.Features:*":[111],"Balances":[112],"presentation":[113,311],"mathematics":[116,314],"processing*":[121],"Algorithms":[122],"numerical":[124,302],"examples":[125,303],"are":[126,304],"implemented":[127,305],"WaveLab,":[129],"a":[130,246,308],"MATLAB":[131,309],"toolbox*":[132],"Companion":[133],"website":[134],"for":[135,143,167,201],"instructors":[136],"selected":[138],"solutions":[139],"code":[141],"available":[142],"studentsNew":[144],"edition*":[147],"Sparse":[148,193],"dictionaries*":[152],"Compressive":[153],"sensing,":[154],"source":[157],"separation*":[158],"Geometric":[159],"image":[160,215,271],"processing":[161,176,218,272,319],"curvelets":[163],"bandlets*":[165],"Wavelets":[166],"computer":[168],"graphics":[169],"lifting":[171],"on":[172],"surfaces*":[173],"Time-frequency":[174],"audio":[175],"denoising*":[178],"Image":[179],"compression":[180],"JPEG-2000*":[182],"New":[183,256],"updated":[185],"exercisesA":[186],"Wavelet":[187],"Tour":[188,278],"Signal":[190,280],"Processing:":[191],"Way,":[194],"third":[195],"edition,":[196],"an":[198,270],"invaluable":[199],"resource":[200],"researchers":[202],"R&D":[204],"engineers":[205],"wishing":[206],"apply":[208],"theory":[210],"fields":[212],"as":[214],"processing,":[216],"video":[217],"bio-sensing,":[221],"medical":[222],"imaging,":[223],"machine":[224],"vision":[225],"communications":[227],"engineering.Stephane":[228],"Mallat":[229],"Professor":[231,247],"Applied":[233],"Mathematics":[234],"at":[235,248,255],"cole":[236],"Polytechnique,":[237],"Paris,":[238],"France.":[239],"From":[240],"1986":[241],"1996":[243],"he":[244,264],"was":[245,290],"Courant":[250],"Institute":[251],"Mathematical":[253],"Sciences":[254],"York":[257],"University,":[258],"between":[260],"2001":[261],"2007,":[263],"co-founded":[265],"became":[267],"CEO":[268],"semiconductor":[273],"company.Companion":[274],"website:":[275],"A":[276],"Numerical":[277],"Processing":[281],"Includes":[282],"latest":[285],"developments":[286],"since":[287],"published":[291],"1999,":[293],"including":[294],"itsapplication":[295],"JPEG":[297],"2000":[298],"MPEG-4Algorithms":[300],"Wavelab,":[307],"toolboxBalances":[310]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":24},{"year":2020,"cited_by_count":30},{"year":2019,"cited_by_count":31},{"year":2018,"cited_by_count":41},{"year":2017,"cited_by_count":47},{"year":2016,"cited_by_count":97},{"year":2015,"cited_by_count":112},{"year":2014,"cited_by_count":84},{"year":2013,"cited_by_count":86},{"year":2012,"cited_by_count":74}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}