{"id":"https://openalex.org/W1990793701","doi":"https://doi.org/10.1109/tip.2013.2280188","title":"Bayesian Learning of Sparse Multiscale Image Representations","display_name":"Bayesian Learning of Sparse Multiscale Image Representations","publication_year":2013,"publication_date":"2013-08-29","ids":{"openalex":"https://openalex.org/W1990793701","doi":"https://doi.org/10.1109/tip.2013.2280188","mag":"1990793701","pmid":"https://pubmed.ncbi.nlm.nih.gov/24002002"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2013.2280188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2013.2280188","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/A5102858836","display_name":"James M. Hughes","orcid":null},"institutions":[{"id":"https://openalex.org/I880641448","display_name":"Luna Innovations (United States)","ror":"https://ror.org/00hnyb151","country_code":"US","type":"company","lineage":["https://openalex.org/I880641448"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Michael Hughes","raw_affiliation_strings":["Applied Research and Technology (ART) group, LGS Innovations, Florham Park, NJ, USA","Appl. Res. & Technol. (ART) Group, LGS Innovations, Florham Park, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied Research and Technology (ART) group, LGS Innovations, Florham Park, NJ, USA","institution_ids":["https://openalex.org/I880641448"]},{"raw_affiliation_string":"Appl. Res. & Technol. (ART) Group, LGS Innovations, Florham Park, NJ, USA","institution_ids":["https://openalex.org/I880641448"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072455364","display_name":"Daniel N. Rockmore","orcid":"https://orcid.org/0000-0001-5411-9224"},"institutions":[{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel N. Rockmore","raw_affiliation_strings":["Dartmouth College, Hanover, NH, US","Department of Math and Computer Science, Dartmouth College, Hanover, NH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dartmouth College, Hanover, NH, US","institution_ids":["https://openalex.org/I107672454"]},{"raw_affiliation_string":"Department of Math and Computer Science, Dartmouth College, Hanover, NH, USA","institution_ids":["https://openalex.org/I107672454"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100423354","display_name":"Yang Wang","orcid":"https://orcid.org/0000-0002-8903-2388"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Wang","raw_affiliation_strings":["Department of Mathematics, Michigan State University, East Lansing, MI, USA","Dept. of Math., Michigan State Univ., East Lansing, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Dept. of Math., Michigan State Univ., East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2638,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.92918652,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"22","issue":"12","first_page":"4972","last_page":"4983"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9997000098228455,"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/T10688","display_name":"Image and Signal Denoising Methods","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":0.9940999746322632,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9939000010490417,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6286669969558716},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6191785335540771},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5922698378562927},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.5495343804359436},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.4996664524078369},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4842643141746521},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.47219738364219666},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4714701473712921},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4582487940788269},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.45000436902046204},{"id":"https://openalex.org/keywords/multiresolution-analysis","display_name":"Multiresolution analysis","score":0.4399992525577545},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.42679911851882935},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42321985960006714},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.41454678773880005},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3856392204761505},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.385061651468277},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.35273486375808716},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2944643795490265},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.1671469807624817}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6286669969558716},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6191785335540771},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5922698378562927},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.5495343804359436},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.4996664524078369},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4842643141746521},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.47219738364219666},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4714701473712921},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4582487940788269},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.45000436902046204},{"id":"https://openalex.org/C121927907","wikidata":"https://www.wikidata.org/wiki/Q1952516","display_name":"Multiresolution analysis","level":5,"score":0.4399992525577545},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.42679911851882935},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42321985960006714},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.41454678773880005},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3856392204761505},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.385061651468277},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.35273486375808716},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2944643795490265},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.1671469807624817},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tip.2013.2280188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2013.2280188","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:24002002","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/24002002","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},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-62638","is_oa":false,"landing_page_url":"http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=LinksAMR&SrcApp=PARTNER_APP&DestLinkType=FullRecord&DestApp=WOS&KeyUT=000325223300033","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:repository.ust.hk:1783.1-62638","is_oa":false,"landing_page_url":"http://repository.ust.hk/ir/Record/1783.1-62638","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1512748702","https://openalex.org/W1517266559","https://openalex.org/W1579303078","https://openalex.org/W1783767608","https://openalex.org/W1971509683","https://openalex.org/W2056758595","https://openalex.org/W2063951063","https://openalex.org/W2078204800","https://openalex.org/W2079724595","https://openalex.org/W2085725062","https://openalex.org/W2086962710","https://openalex.org/W2099321050","https://openalex.org/W2099563019","https://openalex.org/W2100502520","https://openalex.org/W2100592466","https://openalex.org/W2101789093","https://openalex.org/W2103504761","https://openalex.org/W2109627206","https://openalex.org/W2109812093","https://openalex.org/W2110158442","https://openalex.org/W2113606819","https://openalex.org/W2113945798","https://openalex.org/W2114122776","https://openalex.org/W2117111086","https://openalex.org/W2122922389","https://openalex.org/W2124731682","https://openalex.org/W2127320676","https://openalex.org/W2128002512","https://openalex.org/W2128989367","https://openalex.org/W2129534953","https://openalex.org/W2132984323","https://openalex.org/W2134929491","https://openalex.org/W2140433132","https://openalex.org/W2141658583","https://openalex.org/W2143204933","https://openalex.org/W2145889472","https://openalex.org/W2150548620","https://openalex.org/W2151693816","https://openalex.org/W2153663612","https://openalex.org/W2158940042","https://openalex.org/W2160547390","https://openalex.org/W2217045154","https://openalex.org/W2492794003","https://openalex.org/W2990138404","https://openalex.org/W3042002396","https://openalex.org/W4212863985","https://openalex.org/W4214806317","https://openalex.org/W4255521522","https://openalex.org/W4256068510","https://openalex.org/W6681029311","https://openalex.org/W6681304427","https://openalex.org/W6682079006","https://openalex.org/W6688434968","https://openalex.org/W7002382766","https://openalex.org/W7067769601"],"related_works":["https://openalex.org/W2016265625","https://openalex.org/W2111634407","https://openalex.org/W2552089492","https://openalex.org/W4205656132","https://openalex.org/W2008821896","https://openalex.org/W2982240858","https://openalex.org/W2067062989","https://openalex.org/W3004790527","https://openalex.org/W2080187108","https://openalex.org/W2972860561"],"abstract_inverted_index":{"Multiscale":[0],"representations":[1,13,70],"of":[2,17,47,87,101,112,137,140,151,173,188,205,217,222,244],"images":[3],"have":[4,71,93],"become":[5],"a":[6,15,108,128,149,156,185],"standard":[7],"tool":[8],"in":[9,28,198],"image":[10,79,179,236],"analysis.":[11],"Such":[12],"offer":[14],"number":[16],"advantages":[18],"over":[19],"fixed-scale":[20],"methods,":[21],"including":[22,51,219,239],"the":[23,32,113,119,138,170,174,199,220,230],"potential":[24],"for":[25,66,130,214,225],"improved":[26],"performance":[27],"denoising,":[29],"compression,":[30],"and":[31,118,166,212,241],"ability":[33,120],"to":[34,77,106,121,183,233],"represent":[35],"distinct":[36,152],"but":[37,96],"complementary":[38],"information":[39],"that":[40,134,192],"exists":[41],"at":[42,83],"various":[43],"scales.":[44,125],"A":[45],"variety":[46],"multiresolution":[48],"transforms":[49],"exist,":[50],"both":[52],"orthogonal":[53],"decompositions":[54],"such":[55],"as":[56,58,60],"wavelets":[57],"well":[59],"nonorthogonal,":[61],"overcomplete":[62],"representations.":[63],"Recently,":[64],"techniques":[65,103],"finding":[67],"adaptive,":[68],"sparse":[69,167],"yielded":[72,94],"state-of-the-art":[73],"results":[74],"when":[75],"applied":[76],"traditional":[78],"processing":[80,237],"problems.":[81],"Attempts":[82],"developing":[84],"multiscale":[85,114,131],"versions":[86],"these":[88,102],"so-called":[89],"dictionary":[90,115,132,164,190],"learning":[91,116,133,165],"models":[92],"modest":[95],"encouraging":[97],"results.":[98],"However,":[99],"none":[100],"has":[104],"sought":[105],"combine":[107],"rigorous":[109],"statistical":[110,203],"formulation":[111],"problem":[117],"share":[122],"atoms":[123,191],"across":[124],"We":[126,228],"present":[127],"model":[129,180,204,232],"overcomes":[135],"some":[136],"drawbacks":[139],"previous":[141],"approaches":[142],"by":[143],"first":[144],"decomposing":[145],"an":[146],"input":[147],"into":[148],"pyramid":[150],"frequency":[153],"bands":[154],"using":[155],"recursive":[157],"filtering":[158],"scheme,":[159],"after":[160],"which":[161],"we":[162],"perform":[163],"coding":[168],"on":[169],"individual":[171],"levels":[172],"resulting":[175],"pyramid.":[176],"The":[177,201],"associated":[178],"allows":[181,213],"us":[182],"use":[184],"single":[186],"set":[187],"adapted":[189],"is":[193,209],"shared--and":[194],"learned--across":[195],"all":[196],"scales":[197],"model.":[200],"underlying":[202],"our":[206],"proposed":[207,231],"method":[208],"fully":[210],"Bayesian":[211],"efficient":[215],"inference":[216],"parameters,":[218],"level":[221],"additive":[223],"noise":[224],"denoising":[226,243],"applications.":[227],"apply":[229],"several":[234],"common":[235],"problems":[238],"non-Gaussian":[240],"nonstationary":[242],"real-world":[245],"color":[246],"images.":[247]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}