{"id":"https://openalex.org/W2170608472","doi":"https://doi.org/10.1145/2661229.2661262","title":"Spatial-spectral encoded compressive hyperspectral imaging","display_name":"Spatial-spectral encoded compressive hyperspectral imaging","publication_year":2014,"publication_date":"2014-11-18","ids":{"openalex":"https://openalex.org/W2170608472","doi":"https://doi.org/10.1145/2661229.2661262","mag":"2170608472"},"language":"en","primary_location":{"id":"doi:10.1145/2661229.2661262","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2661229.2661262","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-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/A5017194489","display_name":"Xing Lin","orcid":"https://orcid.org/0000-0003-3170-7554"},"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":true,"raw_author_name":"Xing Lin","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032875389","display_name":"Yebin Liu","orcid":"https://orcid.org/0000-0003-3215-0225"},"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":"Yebin Liu","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025651569","display_name":"Jiamin Wu","orcid":"https://orcid.org/0000-0003-3479-1026"},"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":"Jiamin Wu","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080722708","display_name":"Qionghai Dai","orcid":"https://orcid.org/0000-0001-7043-3061"},"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":"Qionghai Dai","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5017194489"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":15.1254,"has_fulltext":false,"cited_by_count":303,"citation_normalized_percentile":{"value":0.9954787,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"33","issue":"6","first_page":"1","last_page":"11"},"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":0.9998000264167786,"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":0.9994999766349792,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8353316783905029},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7077188491821289},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6690612435340881},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6437895894050598},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.5439609885215759},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5262671709060669},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5236651301383972},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.5058593153953552},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4978961944580078},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4967508912086487},{"id":"https://openalex.org/keywords/randomness","display_name":"Randomness","score":0.4422697424888611},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4297294318675995},{"id":"https://openalex.org/keywords/mutual-coherence","display_name":"Mutual coherence","score":0.4141010642051697},{"id":"https://openalex.org/keywords/associative-array","display_name":"Associative array","score":0.41353219747543335},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2625346779823303},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.16584613919258118}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8353316783905029},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7077188491821289},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6690612435340881},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6437895894050598},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.5439609885215759},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5262671709060669},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5236651301383972},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.5058593153953552},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4978961944580078},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4967508912086487},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.4422697424888611},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4297294318675995},{"id":"https://openalex.org/C45900066","wikidata":"https://www.wikidata.org/wiki/Q6944191","display_name":"Mutual coherence","level":3,"score":0.4141010642051697},{"id":"https://openalex.org/C168781493","wikidata":"https://www.wikidata.org/wiki/Q80585","display_name":"Associative array","level":2,"score":0.41353219747543335},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2625346779823303},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.16584613919258118},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2661229.2661262","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2661229.2661262","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1761003969","https://openalex.org/W1970762771","https://openalex.org/W1971319412","https://openalex.org/W1972606091","https://openalex.org/W1975622988","https://openalex.org/W1983892467","https://openalex.org/W1985051078","https://openalex.org/W1991024374","https://openalex.org/W1992653101","https://openalex.org/W1997164347","https://openalex.org/W2000468482","https://openalex.org/W2002498099","https://openalex.org/W2011813002","https://openalex.org/W2012946078","https://openalex.org/W2028781966","https://openalex.org/W2029285847","https://openalex.org/W2030270830","https://openalex.org/W2043460367","https://openalex.org/W2052468738","https://openalex.org/W2064500837","https://openalex.org/W2070145771","https://openalex.org/W2070615500","https://openalex.org/W2073362905","https://openalex.org/W2083042020","https://openalex.org/W2086099702","https://openalex.org/W2088619985","https://openalex.org/W2092116045","https://openalex.org/W2099641086","https://openalex.org/W2102129292","https://openalex.org/W2103613367","https://openalex.org/W2103955025","https://openalex.org/W2107541189","https://openalex.org/W2119967924","https://openalex.org/W2120478201","https://openalex.org/W2129131372","https://openalex.org/W2134033146","https://openalex.org/W2136761288","https://openalex.org/W2144412886","https://openalex.org/W2151364185","https://openalex.org/W2153663612","https://openalex.org/W2155084314","https://openalex.org/W2157343005","https://openalex.org/W2160547390","https://openalex.org/W2163753106","https://openalex.org/W2166785998","https://openalex.org/W2296616510","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W2884878023","https://openalex.org/W2157785665","https://openalex.org/W2972860561","https://openalex.org/W2044636610","https://openalex.org/W2543052009","https://openalex.org/W4210806644","https://openalex.org/W3035632580","https://openalex.org/W2048352340","https://openalex.org/W2284001077","https://openalex.org/W2170608472"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,20,49,65,110],"novel":[4],"compressive":[5,60],"hyperspectral":[6],"(HS)":[7],"imaging":[8,62],"approach":[9,120],"that":[10],"allows":[11],"for":[12,95,135,147],"high-resolution":[13],"HS":[14,36,61,76,93,100,107,133,150,158],"images":[15,77,94,108,134,159],"to":[16,73,104],"be":[17],"captured":[18,126],"in":[19,54,109],"single":[21],"image.":[22],"The":[23],"proposed":[24,119],"architecture":[25],"comprises":[26],"three":[27],"key":[28],"components:":[29],"spatial-spectral":[30,44],"encoded":[31,45],"optical":[32],"camera":[33],"design,":[34],"over-complete":[35,99,149],"dictionary":[37,101,151],"learning":[38],"and":[39,64,124,128,138,152,161],"sparse-constraint":[40],"computational":[41,96],"reconstruction.":[42],"Our":[43],"sampling":[46],"scheme":[47],"provides":[48],"higher":[50,83],"degree":[51],"of":[52,132],"randomness":[53],"the":[55,75,79,87,91,106,118,148],"measured":[56],"projections":[57],"than":[58,113],"previous":[59,114],"approaches;":[63],"robust":[66],"nonlinear":[67],"sparse":[68,153],"reconstruction":[69],"method":[70],"is":[71,102],"employed":[72],"recover":[74],"from":[78],"coded":[80],"projection":[81],"with":[82],"performance.":[84],"To":[85],"exploit":[86],"sparsity":[88],"constraint":[89],"on":[90,121],"nature":[92],"reconstruction,":[97],"an":[98],"learned":[103],"represent":[105],"sparser":[111],"way":[112],"representations.":[115],"We":[116],"validate":[117],"both":[122,136],"synthetic":[123],"real":[125],"data,":[127],"show":[129],"successful":[130],"recovery":[131],"indoor":[137],"outdoor":[139],"scenes.":[140],"In":[141],"addition,":[142],"we":[143],"demonstrate":[144],"other":[145],"applications":[146],"coding":[154],"techniques,":[155],"including":[156],"3D":[157],"compression":[160],"denoising.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":33},{"year":2024,"cited_by_count":47},{"year":2023,"cited_by_count":38},{"year":2022,"cited_by_count":33},{"year":2021,"cited_by_count":28},{"year":2020,"cited_by_count":26},{"year":2019,"cited_by_count":25},{"year":2018,"cited_by_count":25},{"year":2017,"cited_by_count":23},{"year":2016,"cited_by_count":18},{"year":2015,"cited_by_count":6}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}