{"id":"https://openalex.org/W2432740169","doi":"https://doi.org/10.1109/icassp.2013.6638043","title":"Exploiting structural complexity for robust and rapid hyperspectral imaging","display_name":"Exploiting structural complexity for robust and rapid hyperspectral imaging","publication_year":2013,"publication_date":"2013-05-01","ids":{"openalex":"https://openalex.org/W2432740169","doi":"https://doi.org/10.1109/icassp.2013.6638043","mag":"2432740169"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2013.6638043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6638043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1305.2170","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029527167","display_name":"Gregory Ely","orcid":"https://orcid.org/0000-0003-0879-4768"},"institutions":[{"id":"https://openalex.org/I121934306","display_name":"Tufts University","ror":"https://ror.org/05wvpxv85","country_code":"US","type":"education","lineage":["https://openalex.org/I121934306"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Gregory Ely","raw_affiliation_strings":["Department of ECE, Tufts University, Medford, MA, USA","[Department of ECE, Tufts University, Medford, MA, USA]"],"affiliations":[{"raw_affiliation_string":"Department of ECE, Tufts University, Medford, MA, USA","institution_ids":["https://openalex.org/I121934306"]},{"raw_affiliation_string":"[Department of ECE, Tufts University, Medford, MA, USA]","institution_ids":["https://openalex.org/I121934306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004738943","display_name":"Shuchin Aeron","orcid":"https://orcid.org/0000-0002-1049-9795"},"institutions":[{"id":"https://openalex.org/I121934306","display_name":"Tufts University","ror":"https://ror.org/05wvpxv85","country_code":"US","type":"education","lineage":["https://openalex.org/I121934306"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuchin Aeron","raw_affiliation_strings":["Department of ECE, Tufts University, Medford, MA, USA","[Department of ECE, Tufts University, Medford, MA, USA]"],"affiliations":[{"raw_affiliation_string":"Department of ECE, Tufts University, Medford, MA, USA","institution_ids":["https://openalex.org/I121934306"]},{"raw_affiliation_string":"[Department of ECE, Tufts University, Medford, MA, USA]","institution_ids":["https://openalex.org/I121934306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073127824","display_name":"Eric L. Miller","orcid":"https://orcid.org/0000-0002-3156-6002"},"institutions":[{"id":"https://openalex.org/I121934306","display_name":"Tufts University","ror":"https://ror.org/05wvpxv85","country_code":"US","type":"education","lineage":["https://openalex.org/I121934306"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eric L. Miller","raw_affiliation_strings":["Department of ECE, Tufts University, Medford, MA, USA","[Department of ECE, Tufts University, Medford, MA, USA]"],"affiliations":[{"raw_affiliation_string":"Department of ECE, Tufts University, Medford, MA, USA","institution_ids":["https://openalex.org/I121934306"]},{"raw_affiliation_string":"[Department of ECE, Tufts University, Medford, MA, USA]","institution_ids":["https://openalex.org/I121934306"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029527167"],"corresponding_institution_ids":["https://openalex.org/I121934306"],"apc_list":null,"apc_paid":null,"fwci":0.6833064,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.74631836,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2193","last_page":"2197"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.998199999332428,"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":0.9965000152587891,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9168130159378052},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.7033485174179077},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.5708274245262146},{"id":"https://openalex.org/keywords/spectral-imaging","display_name":"Spectral imaging","score":0.5475812554359436},{"id":"https://openalex.org/keywords/tomographic-reconstruction","display_name":"Tomographic reconstruction","score":0.5390517115592957},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5298932194709778},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5069275498390198},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4582170844078064},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4458855390548706},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4388889968395233},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.4279828667640686},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3884198069572449},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3589359223842621},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34830304980278015},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.3376525640487671},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.19970902800559998},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16732215881347656},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.16431060433387756},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.1545197069644928}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9168130159378052},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.7033485174179077},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.5708274245262146},{"id":"https://openalex.org/C3232514","wikidata":"https://www.wikidata.org/wiki/Q7575196","display_name":"Spectral imaging","level":2,"score":0.5475812554359436},{"id":"https://openalex.org/C97742081","wikidata":"https://www.wikidata.org/wiki/Q7820109","display_name":"Tomographic reconstruction","level":3,"score":0.5390517115592957},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5298932194709778},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5069275498390198},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4582170844078064},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4458855390548706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4388889968395233},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.4279828667640686},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3884198069572449},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3589359223842621},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34830304980278015},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3376525640487671},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.19970902800559998},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16732215881347656},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.16431060433387756},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.1545197069644928},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/icassp.2013.6638043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6638043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1305.2170","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1305.2170","pdf_url":"https://arxiv.org/pdf/1305.2170","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"mag:2432740169","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1305.2170.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.744.8913","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.744.8913","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1305.2170.pdf","raw_type":"text"},{"id":"doi:10.48550/arxiv.1305.2170","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1305.2170","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1305.2170","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1305.2170","pdf_url":"https://arxiv.org/pdf/1305.2170","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1968735445","https://openalex.org/W1972112766","https://openalex.org/W1991521292","https://openalex.org/W2031299022","https://openalex.org/W2038858414","https://openalex.org/W2050630265","https://openalex.org/W2050790932","https://openalex.org/W2050880896","https://openalex.org/W2068178468","https://openalex.org/W2069231830","https://openalex.org/W2069306359","https://openalex.org/W2086099702","https://openalex.org/W2098424973","https://openalex.org/W2104767458","https://openalex.org/W2117741752","https://openalex.org/W2119058682","https://openalex.org/W2127077132","https://openalex.org/W2129086087","https://openalex.org/W2142192675","https://openalex.org/W2143701678","https://openalex.org/W2143963681","https://openalex.org/W2145962650","https://openalex.org/W2148717137","https://openalex.org/W2155813684","https://openalex.org/W2160813243","https://openalex.org/W2161073299","https://openalex.org/W6681456887","https://openalex.org/W6682278319"],"related_works":["https://openalex.org/W1998550178","https://openalex.org/W2781745664","https://openalex.org/W2810707356","https://openalex.org/W2745306196","https://openalex.org/W2772985454","https://openalex.org/W3042316989","https://openalex.org/W3013526723","https://openalex.org/W2782463068","https://openalex.org/W2773415061","https://openalex.org/W2790034605","https://openalex.org/W2599914574","https://openalex.org/W1983407583","https://openalex.org/W3183376497","https://openalex.org/W3205930612","https://openalex.org/W2962810499","https://openalex.org/W2607289818","https://openalex.org/W2625388830","https://openalex.org/W2918996790","https://openalex.org/W2159819721","https://openalex.org/W2794188750"],"abstract_inverted_index":{"This":[0,94],"paper":[1],"presents":[2],"several":[3],"strategies":[4],"for":[5,98,99,109],"spectral":[6,28,34,47,61,66],"de-noising":[7],"of":[8,18,79,90,129,140],"hyperspectral":[9,100],"images":[10],"and":[11,63,68,82],"hypercube":[12],"reconstruction":[13],"from":[14],"a":[15,50,80],"limited":[16,120],"number":[17],"tomographic":[19],"measurements.":[20],"In":[21,103],"particular":[22],"we":[23,56,105,132],"show":[24,57,106],"that":[25,58,107],"the":[26,33,39,43,46,59,64,69,77,91,110,134,138],"non-noisy":[27],"data,":[29],"when":[30],"stacked":[31],"across":[32],"dimension,":[35],"exhibits":[36,49],"low-rank.":[37],"On":[38],"other":[40],"hand,":[41],"under":[42,119],"same":[44],"representation,":[45],"noise":[48,67],"banded":[51],"structure.":[52],"Motivated":[53],"by":[54,123],"this":[55],"de-noised":[60],"data":[62],"unknown":[65],"respective":[70],"bands":[71],"can":[72,116],"be":[73,117],"simultaneously":[74],"estimated":[75],"through":[76],"use":[78],"low-rank":[81,125,141],"simultaneous":[83],"sparse":[84],"minimization":[85],"operation":[86],"without":[87],"prior":[88],"knowledge":[89],"noisy":[92],"bands.":[93],"result":[95],"is":[96],"novel":[97],"imaging":[101,108],"applications.":[102],"addition,":[104],"Computed":[111],"Tomography":[112],"Imaging":[113],"Systems":[114],"(CTIS)":[115],"improved":[118],"angle":[121],"tomography":[122],"using":[124,144],"penalization.":[126],"For":[127],"both":[128],"these":[130],"cases":[131],"exploit":[133],"recent":[135],"results":[136],"in":[137],"theory":[139],"matrix":[142],"completion":[143],"nuclear":[145],"norm":[146],"minimization.":[147]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}