{"id":"https://openalex.org/W2116116642","doi":"https://doi.org/10.1109/icip.2002.1038029","title":"Image restoration under wavelet-domain priors: an expectation-maximization approach","display_name":"Image restoration under wavelet-domain priors: an expectation-maximization approach","publication_year":2003,"publication_date":"2003-06-25","ids":{"openalex":"https://openalex.org/W2116116642","doi":"https://doi.org/10.1109/icip.2002.1038029","mag":"2116116642"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2002.1038029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2002.1038029","pdf_url":null,"source":{"id":"https://openalex.org/S4210223844","display_name":"Proceedings - International Conference on Image Processing","issn_l":"1522-4880","issn":["1522-4880","2381-8549"],"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":"Proceedings. International Conference on Image Processing","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/A5026826555","display_name":"M\u00e1rio A. T. Figueiredo","orcid":"https://orcid.org/0000-0002-0970-7745"},"institutions":[{"id":"https://openalex.org/I4387152517","display_name":"Instituto Superior T\u00e9cnico","ror":"https://ror.org/03db2by73","country_code":null,"type":"education","lineage":["https://openalex.org/I141596103","https://openalex.org/I4387152517"]}],"countries":["PT"],"is_corresponding":true,"raw_author_name":"M.A.T. Figueiredo","raw_affiliation_strings":["Institute of Telecommunications, Instituto Superior T\u00e9cnico, Lisboa, Portugal"],"affiliations":[{"raw_affiliation_string":"Institute of Telecommunications, Instituto Superior T\u00e9cnico, Lisboa, Portugal","institution_ids":["https://openalex.org/I4387152517"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030517369","display_name":"Rob Nowak","orcid":null},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R.D. Nowak","raw_affiliation_strings":["Electrical and Computer Engineering Depart, Rice University, Houston, TX, USA"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Depart, Rice University, Houston, TX, USA","institution_ids":["https://openalex.org/I74775410"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026826555"],"corresponding_institution_ids":["https://openalex.org/I4387152517"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.18003731,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"I","last_page":"337"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":1.0,"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":1.0,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.9995999932289124,"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/wavelet","display_name":"Wavelet","score":0.7145609259605408},{"id":"https://openalex.org/keywords/second-generation-wavelet-transform","display_name":"Second-generation wavelet transform","score":0.6342915892601013},{"id":"https://openalex.org/keywords/cascade-algorithm","display_name":"Cascade algorithm","score":0.6031607389450073},{"id":"https://openalex.org/keywords/stationary-wavelet-transform","display_name":"Stationary wavelet transform","score":0.602412223815918},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5973232388496399},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5395179986953735},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.517092227935791},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.5016753673553467},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.4946882426738739},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.47480645775794983},{"id":"https://openalex.org/keywords/deconvolution","display_name":"Deconvolution","score":0.42624977231025696},{"id":"https://openalex.org/keywords/harmonic-wavelet-transform","display_name":"Harmonic wavelet transform","score":0.42572811245918274},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4212311804294586},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41658106446266174},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3512643575668335},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3378908634185791},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.23857948184013367},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23494139313697815}],"concepts":[{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.7145609259605408},{"id":"https://openalex.org/C111350171","wikidata":"https://www.wikidata.org/wiki/Q7443700","display_name":"Second-generation wavelet transform","level":5,"score":0.6342915892601013},{"id":"https://openalex.org/C88829872","wikidata":"https://www.wikidata.org/wiki/Q5048176","display_name":"Cascade algorithm","level":5,"score":0.6031607389450073},{"id":"https://openalex.org/C73339587","wikidata":"https://www.wikidata.org/wiki/Q1375942","display_name":"Stationary wavelet transform","level":5,"score":0.602412223815918},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5973232388496399},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5395179986953735},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.517092227935791},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.5016753673553467},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4946882426738739},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.47480645775794983},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.42624977231025696},{"id":"https://openalex.org/C1109138","wikidata":"https://www.wikidata.org/wiki/Q3280930","display_name":"Harmonic wavelet transform","level":5,"score":0.42572811245918274},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4212311804294586},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41658106446266174},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3512643575668335},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3378908634185791},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.23857948184013367},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23494139313697815},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip.2002.1038029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2002.1038029","pdf_url":null,"source":{"id":"https://openalex.org/S4210223844","display_name":"Proceedings - International Conference on Image Processing","issn_l":"1522-4880","issn":["1522-4880","2381-8549"],"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":"Proceedings. International Conference on Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.10.3326","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.3326","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.lx.it.pt/%7Emtf/ICIP_2002_Figueiredo.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1708257072","https://openalex.org/W1835905189","https://openalex.org/W1989780541","https://openalex.org/W2022905067","https://openalex.org/W2050880896","https://openalex.org/W2053742104","https://openalex.org/W2057020849","https://openalex.org/W2068842398","https://openalex.org/W2070666582","https://openalex.org/W2092543127","https://openalex.org/W2098029226","https://openalex.org/W2106125561","https://openalex.org/W2109502593","https://openalex.org/W2115755118","https://openalex.org/W2117853077","https://openalex.org/W2118459459","https://openalex.org/W2118823201","https://openalex.org/W2124335859","https://openalex.org/W2134929491","https://openalex.org/W2150060382","https://openalex.org/W2156706175","https://openalex.org/W6637641960","https://openalex.org/W6674588189","https://openalex.org/W6676532977"],"related_works":["https://openalex.org/W1986475093","https://openalex.org/W2144408025","https://openalex.org/W1588899229","https://openalex.org/W1976022598","https://openalex.org/W2085792030","https://openalex.org/W1918078477","https://openalex.org/W2391053410","https://openalex.org/W1506615375","https://openalex.org/W2274421086","https://openalex.org/W2387588207"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"an":[3,85],"expectation-maximization":[4],"(EM)":[5],"algorithm":[6,54,82,139],"for":[7,109,126,134],"wavelet-based":[8],"image":[9,14,60],"restoration":[10],"(deconvolution).":[11],"The":[12,52,81,114,132],"observed":[13],"is":[15,31,122],"assumed":[16],"to":[17],"be":[18],"a":[19,35,89,94],"convolved":[20],"(e.g.,":[21],"blurred)":[22],"and":[23,88,128],"noisy":[24],"version":[25],"of":[26,44,49,72,112,136],"the":[27,39,45,58,64,70,73,77,110,119,137],"original":[28],"image.":[29],"Regularization":[30],"achieved":[32],"by":[33,63],"using":[34],"complexity":[36],"penalty/prior":[37],"in":[38,76,93],"wavelet":[40,50,66,127],"domain,":[41],"taking":[42],"advantage":[43],"well":[46],"known":[47],"sparsity":[48],"representations.":[51],"EM":[53,130],"herein":[55],"proposed":[56,138],"combines":[57],"efficient":[59,96],"representation":[61],"offered":[62],"discrete":[65,78],"transform":[67],"(DWT)":[68],"with":[69],"diagonalization":[71],"convolution":[74],"operator":[75],"Fourier":[79,129],"domain.":[80],"alternates":[83],"between":[84],"FFT-based":[86],"E-step":[87],"DWT-based":[90],"M-step,":[91],"resulting":[92],"very":[95],"iterative":[97],"process":[98],"requiring":[99],"O(N":[100],"log":[101],"N)":[102],"operations":[103],"per":[104],"iteration":[105],"(where":[106],"N":[107],"stands":[108],"number":[111],"pixels).":[113],"algorithm,":[115],"which":[116],"also":[117,141],"estimates":[118],"noise":[120],"variance,":[121],"called":[123],"WAFER,":[124],"standing":[125],"restoration.":[131],"conditions":[133],"convergence":[135],"are":[140],"presented.":[142]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}