{"id":"https://openalex.org/W7164414606","doi":"https://doi.org/10.1109/tip.2026.3700920","title":"CSVSUF: A Deep Unfolding Framework for Compressive Spectral Video Sensing","display_name":"CSVSUF: A Deep Unfolding Framework for Compressive Spectral Video Sensing","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7164414606","doi":"https://doi.org/10.1109/tip.2026.3700920","pmid":"https://pubmed.ncbi.nlm.nih.gov/42275332"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2026.3700920","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3700920","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/A5077703661","display_name":"Zhilin Li","orcid":"https://orcid.org/0000-0003-1507-323X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhilin Li","raw_affiliation_strings":["School of Microelectronics, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0000-4568-1186","affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004690476","display_name":"Han Wang","orcid":"https://orcid.org/0000-0002-6938-9574"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Wang","raw_affiliation_strings":["School of Microelectronics, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-6938-9574","affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073882826","display_name":"Jizhong Duan","orcid":"https://orcid.org/0000-0002-5854-6239"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jizhong Duan","raw_affiliation_strings":["Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China"],"raw_orcid":"https://orcid.org/0000-0002-5854-6239","affiliations":[{"raw_affiliation_string":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072835010","display_name":"Baihua Li","orcid":"https://orcid.org/0000-0002-4930-7690"},"institutions":[{"id":"https://openalex.org/I143804889","display_name":"Loughborough University","ror":"https://ror.org/04vg4w365","country_code":"GB","type":"education","lineage":["https://openalex.org/I143804889"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Baihua Li","raw_affiliation_strings":["Department of Computer Science, Loughborough University, Loughborough, U.K"],"raw_orcid":"https://orcid.org/0000-0002-4930-7690","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Loughborough University, Loughborough, U.K","institution_ids":["https://openalex.org/I143804889"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034675261","display_name":"Yu Liu","orcid":"https://orcid.org/0000-0002-5949-6587"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Liu","raw_affiliation_strings":["School of Microelectronics, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-5949-6587","affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.7604208,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"6416","last_page":"6431"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9850000143051147,"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":0.9850000143051147,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.00139999995008111,"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/T11019","display_name":"Image Enhancement Techniques","score":0.0010999999940395355,"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":0.4950999915599823},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3716999888420105},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.36320000886917114},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.35569998621940613},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33410000801086426},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.32710000872612},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.3249000012874603},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.2957000136375427}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6152999997138977},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6054999828338623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5932000279426575},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.4950999915599823},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3716999888420105},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.36320000886917114},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.35569998621940613},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.3249000012874603},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.290800005197525},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.2879999876022339},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.28780001401901245},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.28349998593330383},{"id":"https://openalex.org/C2983668108","wikidata":"https://www.wikidata.org/wiki/Q280453","display_name":"Spectral analysis","level":3,"score":0.2816999852657318},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2026.3700920","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3700920","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:42275332","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42275332","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":[{"id":"https://metadata.un.org/sdg/13","score":0.5363205075263977,"display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G6635624755","display_name":null,"funder_award_id":"22JCZDJC00270","funder_id":"https://openalex.org/F4320323993","funder_display_name":"Natural Science Foundation of Tianjin City"}],"funders":[{"id":"https://openalex.org/F4320323993","display_name":"Natural Science Foundation of Tianjin City","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Spectral":[0],"videos":[1],"(SVs)":[2],"capture":[3,134],"spatio-temporal-spectral":[4,129],"information":[5],"from":[6,41],"dynamic":[7],"scenes,":[8],"but":[9],"their":[10,71],"acquisition":[11],"traditionally":[12],"requires":[13],"expensive":[14],"and":[15,77,94,177],"complex":[16,75],"systems,":[17],"motivating":[18],"the":[19,30,88,101,135,150,181],"development":[20],"of":[21,91,183],"compressive":[22,109],"spectral":[23,34,95,110,121],"video":[24,111,122],"sensing":[25,112],"(CSVS).":[26],"It":[27],"typically":[28],"employs":[29],"coded":[31],"aperture":[32],"snapshot":[33],"imager":[35],"(CASSI)":[36],"to":[37,98,133],"acquire":[38],"compressed":[39],"measurements,":[40],"which":[42,69],"SVs":[43],"are":[44],"reconstructed":[45],"via":[46],"model-driven":[47,63],"or":[48],"learning-based":[49,85],"algorithms.":[50],"However,":[51],"two":[52],"major":[53],"limitations":[54],"remain":[55],"in":[56,74,79,116,153,173,191],"current":[57],"CASSI-based":[58],"reconstruction":[59,175],"methods:":[60],"1)":[61],"conventional":[62],"algorithms":[64],"rely":[65],"on":[66],"iterative":[67],"optimization,":[68],"limits":[70],"representational":[72],"capacity":[73],"scenes":[76],"results":[78],"slow":[80],"reconstruction;":[81],"2)":[82],"existing":[83,171],"deep":[84,158,188],"approaches":[86,172],"overlook":[87],"joint":[89],"modeling":[90,186],"spatial,":[92],"temporal,":[93],"correlations,":[96],"failing":[97],"fully":[99],"exploit":[100],"multi-dimensional":[102,136],"dependencies.":[103],"Hence,":[104],"we":[105,125,155],"propose":[106],"a":[107,117,127,146,157],"principled":[108],"unfolding":[113,140],"framework":[114],"(CSVSUF)":[115],"CASSI":[118],"system":[119],"for":[120,149,161],"reconstruction.":[123],"Moreover,":[124],"develop":[126],"novel":[128],"prior-learning":[130],"Transformer":[131],"(STS-PLT)":[132],"correlations":[137],"within":[138],"each":[139],"stage.":[141],"By":[142],"treating":[143],"STS-PLT":[144],"as":[145],"Gaussian":[147],"denoiser":[148],"prior":[151,189],"term":[152],"CSVSUF,":[154],"establish":[156],"unfolding-based":[159],"method":[160,168],"CSVS.":[162,192],"Extensive":[163],"experiments":[164],"demonstrate":[165],"that":[166],"our":[167],"consistently":[169],"outperforms":[170],"both":[174],"accuracy":[176],"visual":[178],"quality,":[179],"validating":[180],"benefit":[182],"combining":[184],"physics-guided":[185],"with":[187],"learning":[190],"Code":[193],"is":[194],"available":[195],"at":[196],"https://github.com/zli1024/CSVSUF.":[197]},"counts_by_year":[],"updated_date":"2026-06-20T20:08:15.867695","created_date":"2026-06-12T00:00:00"}
