{"id":"https://openalex.org/W1582456702","doi":"https://doi.org/10.1109/pcs.2015.7170089","title":"Large-scale structured sparse image reconstruction with correlated multiple-measurement vectors using Bayesian learning","display_name":"Large-scale structured sparse image reconstruction with correlated multiple-measurement vectors using Bayesian learning","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1582456702","doi":"https://doi.org/10.1109/pcs.2015.7170089","mag":"1582456702"},"language":"en","primary_location":{"id":"doi:10.1109/pcs.2015.7170089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pcs.2015.7170089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Picture Coding Symposium (PCS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100632412","display_name":"Shaoyang Li","orcid":"https://orcid.org/0009-0008-1612-0740"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoyang Li","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","State Key Laboratory on Microwave and Digital Communications,Tsinghua National Laboratory for Information Science and Technology,Department of Electronic Engineering,Tsinghua University,Beijing 100084,China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"State Key Laboratory on Microwave and Digital Communications,Tsinghua National Laboratory for Information Science and Technology,Department of Electronic Engineering,Tsinghua University,Beijing 100084,China)","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101459083","display_name":"Xiaoming Tao","orcid":"https://orcid.org/0000-0003-2168-0044"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoming Tao","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","State Key Laboratory on Microwave and Digital Communications,Tsinghua National Laboratory for Information Science and Technology,Department of Electronic Engineering,Tsinghua University,Beijing 100084,China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"State Key Laboratory on Microwave and Digital Communications,Tsinghua National Laboratory for Information Science and Technology,Department of Electronic Engineering,Tsinghua University,Beijing 100084,China)","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115602293","display_name":"Yang Li","orcid":"https://orcid.org/0000-0003-4616-4230"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","State Key Laboratory on Microwave and Digital Communications,Tsinghua National Laboratory for Information Science and Technology,Department of Electronic Engineering,Tsinghua University,Beijing 100084,China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"State Key Laboratory on Microwave and Digital Communications,Tsinghua National Laboratory for Information Science and Technology,Department of Electronic Engineering,Tsinghua University,Beijing 100084,China)","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053012932","display_name":"Jianhua L\u00fc","orcid":"https://orcid.org/0000-0002-0314-9172"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Lu","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","State Key Laboratory on Microwave and Digital Communications,Tsinghua National Laboratory for Information Science and Technology,Department of Electronic Engineering,Tsinghua University,Beijing 100084,China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"State Key Laboratory on Microwave and Digital Communications,Tsinghua National Laboratory for Information Science and Technology,Department of Electronic Engineering,Tsinghua University,Beijing 100084,China)","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.1479,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.73951743,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"272","last_page":"276"},"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/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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9990000128746033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6487482786178589},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6430281400680542},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.640400230884552},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5862957239151001},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5435371994972229},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5429853796958923},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5161441564559937},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4959624707698822},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4875440299510956},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4821183681488037},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37726953625679016},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2491709589958191}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6487482786178589},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6430281400680542},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.640400230884552},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5862957239151001},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5435371994972229},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5429853796958923},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5161441564559937},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4959624707698822},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4875440299510956},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4821183681488037},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37726953625679016},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2491709589958191},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pcs.2015.7170089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pcs.2015.7170089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Picture Coding Symposium (PCS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.47999998927116394,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1601795611","https://openalex.org/W1613135907","https://openalex.org/W1663973292","https://openalex.org/W1770500012","https://openalex.org/W1977423147","https://openalex.org/W1981157266","https://openalex.org/W2020282020","https://openalex.org/W2024153789","https://openalex.org/W2101580881","https://openalex.org/W2145096794","https://openalex.org/W2146000945","https://openalex.org/W2152279006","https://openalex.org/W2157544223","https://openalex.org/W2161610387","https://openalex.org/W2162409952","https://openalex.org/W2164696938","https://openalex.org/W2296616510","https://openalex.org/W3101032515","https://openalex.org/W4250955649","https://openalex.org/W6636306374"],"related_works":["https://openalex.org/W2382174632","https://openalex.org/W2129959498","https://openalex.org/W2784060934","https://openalex.org/W2902714807","https://openalex.org/W2537489131","https://openalex.org/W2394084632","https://openalex.org/W2358293514","https://openalex.org/W2046633342","https://openalex.org/W2059273319","https://openalex.org/W2014650515"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,38,95],"Bayesian":[4],"learning":[5],"approach":[6],"to":[7,14,42,73,100],"structured":[8,71,102],"sparse":[9,103],"image":[10,35,55,63,104],"reconstruction.":[11,105],"In":[12],"contrast":[13],"conventional":[15],"paradigms":[16],"which":[17],"convert":[18],"images":[19],"into":[20,37],"high-dimensional":[21],"vectors":[22],"and":[23,58,93,97],"thus":[24],"are":[25],"impractical":[26],"for":[27],"recovering":[28],"large-scale":[29,101],"images,":[30],"we":[31,48],"formulate":[32],"columns":[33],"of":[34,54,62,90],"matrices":[36,64],"multiple-measurement-vector":[39],"(MMV)":[40],"model":[41],"reduce":[43],"the":[44,51,59],"problem":[45],"dimension.":[46],"Besides,":[47],"simultaneously":[49],"exploit":[50],"tree":[52],"structure":[53],"wavelet":[56,66],"coefficients":[57],"column":[60],"correlations":[61],"in":[65,88],"domain":[67],"as":[68],"two":[69],"prior":[70],"constraints":[72],"improve":[74],"reconstruction":[75,91],"accuracy.":[76],"Experimental":[77],"results":[78],"reveal":[79],"that":[80],"our":[81],"method":[82],"significantly":[83],"outperforms":[84],"other":[85],"MMV-based":[86],"strategies":[87],"terms":[89],"error":[92],"provides":[94],"practical":[96],"efficient":[98],"alternative":[99]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}