{"id":"https://openalex.org/W2953691411","doi":"https://doi.org/10.1109/whispers.2018.8747037","title":"Gas Plume Detection in Hyperspectral Video Sequence Using Tensor Nuclear Norm","display_name":"Gas Plume Detection in Hyperspectral Video Sequence Using Tensor Nuclear Norm","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2953691411","doi":"https://doi.org/10.1109/whispers.2018.8747037","mag":"2953691411"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2018.8747037","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2018.8747037","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-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/A5101845584","display_name":"Wenting Shang","orcid":"https://orcid.org/0000-0002-7315-388X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenting Shang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031361250","display_name":"Zebin Wu","orcid":"https://orcid.org/0000-0002-7162-0202"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zebin Wu","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081204417","display_name":"Wei Jie","orcid":"https://orcid.org/0000-0002-5392-0009"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wei","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102744301","display_name":"Yang Xu","orcid":"https://orcid.org/0000-0002-5499-3728"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Xu","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103211253","display_name":"Ling Qian","orcid":"https://orcid.org/0000-0001-5661-1722"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Qian","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070343691","display_name":"Zhihui Wei","orcid":"https://orcid.org/0000-0002-4841-6051"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihui Wei","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106124934","display_name":"Jocelyn Chanussot","orcid":"https://orcid.org/0000-0003-4817-2875"},"institutions":[{"id":"https://openalex.org/I4210124956","display_name":"Grenoble Images Parole Signal Automatique","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jocelyn Chanussot","raw_affiliation_strings":["GIPSA-Lab, Grenoble Institute of Technology, France"],"affiliations":[{"raw_affiliation_string":"GIPSA-Lab, Grenoble Institute of Technology, France","institution_ids":["https://openalex.org/I106785703","https://openalex.org/I4210124956"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090707978","display_name":"Andrea L. Bertozzi","orcid":"https://orcid.org/0000-0003-0396-7391"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrea L. Bertozzi","raw_affiliation_strings":["Department of Mathematics, University of California, Los Angeles (UCLA), USA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of California, Los Angeles (UCLA), USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5101845584"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.22701538,"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":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"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":0.9990000128746033,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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":0.7475094199180603},{"id":"https://openalex.org/keywords/plume","display_name":"Plume","score":0.6588572859764099},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.5796857476234436},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5422651767730713},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4787401556968689},{"id":"https://openalex.org/keywords/structure-tensor","display_name":"Structure tensor","score":0.4430704116821289},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4429854452610016},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4306175112724304},{"id":"https://openalex.org/keywords/augmented-lagrangian-method","display_name":"Augmented Lagrangian method","score":0.4292405843734741},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4104878604412079},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3885810971260071},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3811383843421936},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3385545015335083},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33603185415267944},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1409148871898651},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12273868918418884},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.12122499942779541},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.09617367386817932}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7475094199180603},{"id":"https://openalex.org/C2775840915","wikidata":"https://www.wikidata.org/wiki/Q3817528","display_name":"Plume","level":2,"score":0.6588572859764099},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.5796857476234436},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5422651767730713},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4787401556968689},{"id":"https://openalex.org/C113315163","wikidata":"https://www.wikidata.org/wiki/Q7625159","display_name":"Structure tensor","level":3,"score":0.4430704116821289},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4429854452610016},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4306175112724304},{"id":"https://openalex.org/C150452318","wikidata":"https://www.wikidata.org/wiki/Q4820432","display_name":"Augmented Lagrangian method","level":2,"score":0.4292405843734741},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4104878604412079},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3885810971260071},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3811383843421936},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3385545015335083},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33603185415267944},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1409148871898651},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12273868918418884},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.12122499942779541},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.09617367386817932},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2018.8747037","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2018.8747037","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2021080560","https://openalex.org/W2059639989","https://openalex.org/W2175634846","https://openalex.org/W2298307030","https://openalex.org/W2512654947","https://openalex.org/W2773266593","https://openalex.org/W2964214749","https://openalex.org/W6747014644"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W2969683494","https://openalex.org/W2330046496","https://openalex.org/W2079558799","https://openalex.org/W4387803809","https://openalex.org/W3022405224","https://openalex.org/W2204885273"],"abstract_inverted_index":{"Gas":[0],"plume":[1,145,158],"detection":[2,136,159,176],"(GPD)":[3],"of":[4,17,37,51,61,93,105,121,142,156,178],"Hyperspectral":[5],"video":[6,28,64],"sequences":[7],"(HVSs)":[8],"has":[9],"become":[10],"a":[11,30,48,69,127],"hot":[12],"topic":[13],"in":[14,78,115,133,146],"the":[15,26,57,62,73,84,90,94,103,106,113,122,134,140,143,150,172,179],"field":[16],"remote":[18],"sensing.":[19],"The":[20,152],"traditional":[21],"HVS":[22,79],"processing":[23],"methods":[24],"reshape":[25],"extracted":[27,63],"to":[29,88,101],"2-D":[31],"matrix,":[32],"which":[33],"is":[34,160],"at":[35],"expense":[36],"destroying":[38],"spatial":[39,74,117],"or":[40],"spectral":[41],"structure.":[42],"In":[43],"this":[44],"paper,":[45],"we":[46,125],"propose":[47],"novel":[49],"method":[50],"Multi-feature":[52],"Tensor":[53],"Decomposition":[54],"(MTD),":[55],"where":[56],"3-dimensional":[58],"(3-D)":[59],"structure":[60],"can":[65],"be":[66],"seen":[67],"as":[68],"3-order":[70],"tensor,":[71],"thus":[72],"and":[75,96,118,138,174],"temporal":[76,119],"structures":[77],"are":[80,149],"preserved.":[81],"We":[82],"employ":[83],"tensor":[85,98],"nuclear":[86],"norm":[87,100],"model":[89],"low-rank":[91],"property":[92],"background,":[95],"apply":[97],"sparse":[99],"constrain":[102],"sparsity":[104],"gas":[107,123,144,157],"plume.":[108],"Moreover,":[109],"taking":[110],"into":[111],"consideration":[112],"continuity":[114],"both":[116],"domain":[120],"plume,":[124],"add":[126],"3-D":[128],"total":[129],"variation":[130],"regularization":[131],"(3DTV)":[132],"proposed":[135,180],"model,":[137],"assume":[139],"support":[141],"different":[147],"features":[148],"same.":[151],"final":[153],"objective":[154],"function":[155],"efficiently":[161],"solved":[162],"by":[163],"augmented":[164],"Lagrangian":[165],"multiplier":[166],"algorithm":[167],"(ADMM).":[168],"Experimental":[169],"results":[170],"demonstrate":[171],"effectiveness":[173],"high":[175],"accuracy":[177],"method.":[181]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}