{"id":"https://openalex.org/W2102129292","doi":"https://doi.org/10.1109/tip.2009.2022459","title":"Learning to Sense Sparse Signals: Simultaneous Sensing Matrix and Sparsifying Dictionary Optimization","display_name":"Learning to Sense Sparse Signals: Simultaneous Sensing Matrix and Sparsifying Dictionary Optimization","publication_year":2009,"publication_date":"2009-06-02","ids":{"openalex":"https://openalex.org/W2102129292","doi":"https://doi.org/10.1109/tip.2009.2022459","mag":"2102129292","pmid":"https://pubmed.ncbi.nlm.nih.gov/19497818"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2009.2022459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2009.2022459","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/A5079244629","display_name":"Julio M. Duarte\u2010Carvajalino","orcid":"https://orcid.org/0000-0001-7117-2051"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"J.M. Duarte-Carvajalino","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455-0436, USA","Dept. of Electr. & Comput. Eng., Univ. of Minnesota, Minneapolis, MN"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455-0436, USA","institution_ids":[]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of Minnesota, Minneapolis, MN","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019781259","display_name":"Guillermo Sapiro","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"G. Sapiro","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA","Dept. of Electr. & Comput. Eng., Univ. of Minnesota, Minneapolis, MN"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of Minnesota, Minneapolis, MN","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5079244629"],"corresponding_institution_ids":["https://openalex.org/I130238516"],"apc_list":null,"apc_paid":null,"fwci":27.8192,"has_fulltext":false,"cited_by_count":575,"citation_normalized_percentile":{"value":0.99784285,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"18","issue":"7","first_page":"1395","last_page":"1408"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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":0.9987000226974487,"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/compressed-sensing","display_name":"Compressed sensing","score":0.8003857731819153},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.6355909109115601},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6217999458312988},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5565311312675476},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5099824666976929},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5079737305641174},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.5060881972312927},{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.5027081966400146},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.49795079231262207},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4944131374359131},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4877477288246155},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4605969190597534},{"id":"https://openalex.org/keywords/random-projection","display_name":"Random projection","score":0.4471837282180786},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.43475961685180664},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.42182672023773193},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35378700494766235},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.18609026074409485},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.08759933710098267}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.8003857731819153},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.6355909109115601},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6217999458312988},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5565311312675476},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5099824666976929},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5079737305641174},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.5060881972312927},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.5027081966400146},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.49795079231262207},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4944131374359131},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4877477288246155},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4605969190597534},{"id":"https://openalex.org/C2777036070","wikidata":"https://www.wikidata.org/wiki/Q18393452","display_name":"Random projection","level":2,"score":0.4471837282180786},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.43475961685180664},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.42182672023773193},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35378700494766235},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.18609026074409485},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.08759933710098267},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2009.2022459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2009.2022459","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:19497818","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/19497818","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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W18046889","https://openalex.org/W1551219034","https://openalex.org/W1608874367","https://openalex.org/W1753871439","https://openalex.org/W1972959470","https://openalex.org/W1985324531","https://openalex.org/W1986931325","https://openalex.org/W2008231398","https://openalex.org/W2020390700","https://openalex.org/W2051496066","https://openalex.org/W2056758595","https://openalex.org/W2082855665","https://openalex.org/W2097713019","https://openalex.org/W2099100030","https://openalex.org/W2101349782","https://openalex.org/W2105464873","https://openalex.org/W2105877514","https://openalex.org/W2113383757","https://openalex.org/W2114122776","https://openalex.org/W2115755118","https://openalex.org/W2116148865","https://openalex.org/W2119667497","https://openalex.org/W2120991191","https://openalex.org/W2121927366","https://openalex.org/W2122548617","https://openalex.org/W2122922389","https://openalex.org/W2127271355","https://openalex.org/W2128638419","https://openalex.org/W2128659236","https://openalex.org/W2129131372","https://openalex.org/W2129812935","https://openalex.org/W2134033146","https://openalex.org/W2136235822","https://openalex.org/W2139427956","https://openalex.org/W2139643804","https://openalex.org/W2140499889","https://openalex.org/W2140609183","https://openalex.org/W2142940228","https://openalex.org/W2143132653","https://openalex.org/W2145096794","https://openalex.org/W2145263492","https://openalex.org/W2145607950","https://openalex.org/W2151693816","https://openalex.org/W2152281536","https://openalex.org/W2153663612","https://openalex.org/W2154332973","https://openalex.org/W2155665608","https://openalex.org/W2156043924","https://openalex.org/W2158162781","https://openalex.org/W2160547390","https://openalex.org/W2164647001","https://openalex.org/W2294576049","https://openalex.org/W2296616510","https://openalex.org/W2532338691","https://openalex.org/W2535202871","https://openalex.org/W2953139536","https://openalex.org/W3070706509","https://openalex.org/W3150180288","https://openalex.org/W4238744307","https://openalex.org/W4250955649","https://openalex.org/W6678757208","https://openalex.org/W6728843030"],"related_works":["https://openalex.org/W2078080292","https://openalex.org/W2583520174","https://openalex.org/W2364118486","https://openalex.org/W2102075063","https://openalex.org/W2111634407","https://openalex.org/W2084716923","https://openalex.org/W2328330214","https://openalex.org/W204290405","https://openalex.org/W2161305109","https://openalex.org/W2982240858"],"abstract_inverted_index":{"Sparse":[0],"signal":[1,17],"representation,":[2],"analysis,":[3],"and":[4,20,54,57,172,184,202,250],"sensing":[5,67,101,135,186,200,226,243],"have":[6],"received":[7],"a":[8,31,38,42,100,111,133,142,166,175,229,241],"lot":[9],"of":[10,34,41,65,121,127,145,159,177,180,198,209,212,217,224,237,247],"attention":[11],"in":[12,52,92],"recent":[13],"years":[14],"from":[15,45,77,174],"the":[16,35,60,63,85,117,124,130,150,156,169,181,185,196,210,213,218,222,225,235,238,248],"processing,":[18],"optimization,":[19,173],"learning":[21,26,211],"communities.":[22],"On":[23,59,129],"one":[24],"hand,":[25,62,132],"overcomplete":[27],"dictionaries":[28],"that":[29,71,137,190,205],"facilitate":[30],"sparse":[32,72],"representation":[33],"data":[36],"as":[37,232,234],"liner":[39],"combination":[40],"few":[43],"atoms":[44],"such":[46],"dictionary":[47,183,231,239],"leads":[48],"to":[49,95],"state-of-the-art":[50],"results":[51],"image":[53,262],"video":[55],"restoration":[56],"classification.":[58],"other":[61,131],"framework":[64,167,220,249],"compressed":[66],"(CS)":[68],"has":[69,105],"shown":[70,107],"signals":[73,146],"can":[74,147],"be":[75],"recovered":[76],"far":[78],"less":[79],"samples":[80,90],"than":[81],"those":[82,203],"required":[83],"by":[84,99],"classical":[86,261],"Shannon-Nyquist":[87],"Theorem.":[88],"The":[89,245],"used":[91],"CS":[93],"correspond":[94],"linear":[96],"projections":[97],"obtained":[98],"projection":[102,134],"matrix.":[103,187],"It":[104],"been":[106],"that,":[108],"for":[109,141,168,228,240],"example,":[110],"nonadaptive":[112],"random":[113,199],"sampling":[114],"matrix":[115,136,227],"satisfies":[116],"fundamental":[118],"theoretical":[119],"requirements":[120],"CS,":[122],"enjoying":[123],"additional":[125],"benefit":[126],"universality.":[128],"is":[138,255],"optimally":[139],"designed":[140],"certain":[143],"class":[144],"further":[148,154],"improve":[149],"reconstruction":[151],"accuracy":[152],"or":[153],"reduce":[155],"necessary":[157],"number":[158],"samples.":[160],"In":[161],"this":[162,191],"paper,":[163],"we":[164],"introduce":[165],"joint":[170,192],"design":[171],"set":[176],"training":[178],"images,":[179],"nonparametric":[182],"We":[188],"show":[189],"optimization":[193,223,236,254],"outperforms":[194],"both":[195],"use":[197],"matrices":[201,204],"are":[206],"optimized":[207],"independently":[208],"dictionary.":[214],"Particular":[215],"cases":[216],"proposed":[219],"include":[221],"given":[230],"well":[233],"predefined":[242],"environment.":[244],"presentation":[246],"its":[251],"efficient":[252],"numerical":[253],"complemented":[256],"with":[257],"numerous":[258],"examples":[259],"on":[260],"datasets.":[263]},"counts_by_year":[{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":19},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":36},{"year":2020,"cited_by_count":39},{"year":2019,"cited_by_count":46},{"year":2018,"cited_by_count":51},{"year":2017,"cited_by_count":52},{"year":2016,"cited_by_count":55},{"year":2015,"cited_by_count":51},{"year":2014,"cited_by_count":52},{"year":2013,"cited_by_count":49},{"year":2012,"cited_by_count":25}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}