{"id":"https://openalex.org/W2557930815","doi":"https://doi.org/10.1109/tip.2016.2633941","title":"Guided Wavelet Shrinkage for Edge-Aware Smoothing","display_name":"Guided Wavelet Shrinkage for Edge-Aware Smoothing","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2557930815","doi":"https://doi.org/10.1109/tip.2016.2633941","mag":"2557930815","pmid":"https://pubmed.ncbi.nlm.nih.gov/27913350"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2016.2633941","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2016.2633941","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5086801148","display_name":"Guang Deng","orcid":"https://orcid.org/0000-0003-1803-4578"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Guang Deng","raw_affiliation_strings":["Department of Engineering, La Trobe University, Bundoora, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Engineering, La Trobe University, Bundoora, VIC, Australia","institution_ids":["https://openalex.org/I196829312"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5086801148"],"corresponding_institution_ids":["https://openalex.org/I196829312"],"apc_list":null,"apc_paid":null,"fwci":1.336,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.87235471,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"26","issue":"2","first_page":"900","last_page":"914"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement 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"}},"topics":[{"id":"https://openalex.org/T11019","display_name":"Image Enhancement 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"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9994999766349792,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"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/smoothing","display_name":"Smoothing","score":0.829865038394928},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.8041801452636719},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.6366673111915588},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5700917840003967},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46497631072998047},{"id":"https://openalex.org/keywords/cascade-algorithm","display_name":"Cascade algorithm","score":0.42374980449676514},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.3749169707298279},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36371731758117676},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3420200049877167},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.33892685174942017},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3376781642436981}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.829865038394928},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.8041801452636719},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.6366673111915588},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5700917840003967},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46497631072998047},{"id":"https://openalex.org/C88829872","wikidata":"https://www.wikidata.org/wiki/Q5048176","display_name":"Cascade algorithm","level":5,"score":0.42374980449676514},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.3749169707298279},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36371731758117676},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3420200049877167},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33892685174942017},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3376781642436981}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2016.2633941","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2016.2633941","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:27913350","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/27913350","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W168460524","https://openalex.org/W1529155083","https://openalex.org/W1536200267","https://openalex.org/W1873172440","https://openalex.org/W1918250297","https://openalex.org/W1963816084","https://openalex.org/W1967795753","https://openalex.org/W1972163814","https://openalex.org/W1973207753","https://openalex.org/W1976452778","https://openalex.org/W1983044509","https://openalex.org/W1995031544","https://openalex.org/W1995194116","https://openalex.org/W1998419211","https://openalex.org/W2015207482","https://openalex.org/W2019904315","https://openalex.org/W2030716039","https://openalex.org/W2033911870","https://openalex.org/W2034588920","https://openalex.org/W2057477395","https://openalex.org/W2061052400","https://openalex.org/W2067191022","https://openalex.org/W2079724595","https://openalex.org/W2088616581","https://openalex.org/W2096768337","https://openalex.org/W2099244020","https://openalex.org/W2105364438","https://openalex.org/W2119445186","https://openalex.org/W2125186487","https://openalex.org/W2125188192","https://openalex.org/W2129276048","https://openalex.org/W2131408363","https://openalex.org/W2141957843","https://openalex.org/W2146842127","https://openalex.org/W2160451035","https://openalex.org/W2166493908","https://openalex.org/W2168896212","https://openalex.org/W2170885533","https://openalex.org/W2213398264","https://openalex.org/W2231495490","https://openalex.org/W2996868574","https://openalex.org/W4247811648","https://openalex.org/W4248081355","https://openalex.org/W4255521522","https://openalex.org/W6606877702","https://openalex.org/W6631983884","https://openalex.org/W6689586722"],"related_works":["https://openalex.org/W4245508182","https://openalex.org/W2001666425","https://openalex.org/W2370050053","https://openalex.org/W2372936409","https://openalex.org/W2046633342","https://openalex.org/W2968739105","https://openalex.org/W2085792030","https://openalex.org/W2351059076","https://openalex.org/W2389645710","https://openalex.org/W2391053410"],"abstract_inverted_index":{"Edge-aware":[0],"smoothing":[1,27,41],"has":[2],"been":[3,22],"extensively":[4],"studied":[5],"due":[6],"to":[7,79,138],"its":[8],"wide":[9],"range":[10],"of":[11,66],"applications":[12],"in":[13,29,51,77,96,140],"computer":[14],"vision":[15],"and":[16,73,83,107,148],"graphics.":[17],"Most":[18],"published":[19],"works":[20],"have":[21,101],"focused":[23],"on":[24,69],"formulating":[25],"the":[26,30,52,70,74,89,97,110,116,122,155],"problem":[28],"spatial":[31],"domain.":[32,99],"In":[33],"this":[34],"paper,":[35],"we":[36],"propose":[37],"a":[38,56,58,64],"new":[39],"edge-aware":[40],"framework":[42],"called":[43],"guided":[44],"wavelet":[45,53,98,105,113],"shrinkage":[46],"(GWS),":[47],"which":[48],"is":[49,115],"formulated":[50],"domain":[54],"as":[55,127],"maximum":[57],"posterior":[59],"estimation":[60],"problem.":[61],"We":[62,87,100,119],"impose":[63],"number":[65],"desirable":[67],"properties":[68],"statistical":[71],"models":[72],"associated":[75],"parameters":[76],"order":[78],"derive":[80],"an":[81,141],"effective":[82],"computationally":[84],"efficient":[85],"algorithm.":[86],"compare":[88],"proposed":[90],"GWS":[91,123],"with":[92,150,162],"classical":[93],"image":[94],"denoising":[95],"also":[102,135],"compared":[103],"different":[104],"representations":[106],"found":[108],"that":[109,121,154],"double-density":[111],"dual-tree":[112],"transform":[114],"best":[117],"choice.":[118],"show":[120],"can":[124,134,158],"be":[125,136],"configured":[126,137],"either":[128],"self-guidance":[129],"or":[130,143],"external":[131],"guidance.":[132],"It":[133],"operate":[139],"iterative":[142],"non-iterative":[144],"way.":[145],"Experimental":[146],"results":[147,161],"comparison":[149],"many":[151],"state-of-the-algorithms":[152],"demonstrate":[153],"GWS-based":[156],"algorithm":[157],"produce":[159],"competitive":[160],"O(N)":[163],"computational":[164],"complexity.":[165]},"counts_by_year":[{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
