{"id":"https://openalex.org/W3129473549","doi":"https://doi.org/10.1109/igarss39084.2020.9323489","title":"Joint Mixed-Noise Removal and Compressed Sensing Reconstruction of Hyperspectral Images via Convex Optimization","display_name":"Joint Mixed-Noise Removal and Compressed Sensing Reconstruction of Hyperspectral Images via Convex Optimization","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3129473549","doi":"https://doi.org/10.1109/igarss39084.2020.9323489","mag":"3129473549"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9323489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","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/A5073256619","display_name":"Saori Takeyama","orcid":"https://orcid.org/0000-0002-8282-2491"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Saori Takeyama","raw_affiliation_strings":["Tokyo Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040341698","display_name":"Shunsuke Ono","orcid":"https://orcid.org/0000-0001-7890-5131"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shunsuke Ono","raw_affiliation_strings":["Tokyo Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5073256619"],"corresponding_institution_ids":["https://openalex.org/I114531698"],"apc_list":null,"apc_paid":null,"fwci":1.2324,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.76851624,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"1","issue":null,"first_page":"1492","last_page":"1495"},"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":0.9998000264167786,"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":0.9997000098228455,"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/compressed-sensing","display_name":"Compressed sensing","score":0.831367015838623},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.761529803276062},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6540428400039673},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6511514782905579},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6280572414398193},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.5823978185653687},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5525373220443726},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5486676096916199},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.5273706912994385},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4921990931034088},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.47924259305000305},{"id":"https://openalex.org/keywords/shot-noise","display_name":"Shot noise","score":0.4649914801120758},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.45049750804901123},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.44830456376075745},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.422058641910553},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.3920063078403473},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.374059796333313},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37392741441726685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2841203510761261},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.270166277885437},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.2036549150943756},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.09191575646400452},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06883788108825684},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.061524420976638794}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.831367015838623},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.761529803276062},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6540428400039673},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6511514782905579},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6280572414398193},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.5823978185653687},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5525373220443726},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5486676096916199},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5273706912994385},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4921990931034088},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.47924259305000305},{"id":"https://openalex.org/C72659945","wikidata":"https://www.wikidata.org/wiki/Q1503574","display_name":"Shot noise","level":3,"score":0.4649914801120758},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.45049750804901123},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.44830456376075745},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.422058641910553},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.3920063078403473},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.374059796333313},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37392741441726685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2841203510761261},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.270166277885437},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2036549150943756},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.09191575646400452},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06883788108825684},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.061524420976638794},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss39084.2020.9323489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W54434497","https://openalex.org/W205960364","https://openalex.org/W1532610010","https://openalex.org/W1593447321","https://openalex.org/W1667895010","https://openalex.org/W2010319424","https://openalex.org/W2039596145","https://openalex.org/W2049189005","https://openalex.org/W2079319869","https://openalex.org/W2092663520","https://openalex.org/W2119449648","https://openalex.org/W2120991191","https://openalex.org/W2123031198","https://openalex.org/W2131697388","https://openalex.org/W2142843085","https://openalex.org/W2145096794","https://openalex.org/W2289756263","https://openalex.org/W2296616510","https://openalex.org/W2517364869","https://openalex.org/W2578004414","https://openalex.org/W2594827121","https://openalex.org/W2628535015","https://openalex.org/W2765202580","https://openalex.org/W2790528326","https://openalex.org/W2802729498","https://openalex.org/W2891364229","https://openalex.org/W2937817153","https://openalex.org/W2965376428","https://openalex.org/W3106359998","https://openalex.org/W4229650096","https://openalex.org/W4250955649","https://openalex.org/W6602248423","https://openalex.org/W6735339649","https://openalex.org/W6745193812"],"related_works":["https://openalex.org/W2118587210","https://openalex.org/W2499334499","https://openalex.org/W2994944367","https://openalex.org/W2147704231","https://openalex.org/W3164401114","https://openalex.org/W2986378528","https://openalex.org/W3178345791","https://openalex.org/W1656055395","https://openalex.org/W2092661960","https://openalex.org/W1550854977"],"abstract_inverted_index":{"Compressed":[0],"sensing":[1],"(CS)":[2],"reconstruction":[3],"is":[4,24],"essential":[5],"in":[6],"capturing":[7],"hyperspectral":[8],"(HS)":[9],"images":[10],"by":[11,26,76],"one-shot.":[12],"However,":[13],"existing":[14],"approaches":[15],"for":[16],"compressed":[17,22,52],"HS":[18,53,71],"imaging":[19,54],"assume":[20],"that":[21,55],"observation":[23],"contaminated":[25],"Gaussian":[27],"noise,":[28],"and":[29,40,73],"so":[30],"they":[31],"are":[32],"sensitive":[33],"to":[34],"the":[35,44,85],"other":[36],"type":[37],"of":[38,87],"noise":[39,75],"outliers.":[41],"To":[42],"resolve":[43],"above":[45],"problem,":[46],"we":[47],"propose":[48],"a":[49,69,78],"new":[50],"methodology":[51],"can":[56],"handle":[57],"mixed":[58],"Gaussian-sparse":[59],"noise.":[60],"For":[61],"robust":[62],"estimation,":[63],"our":[64,88],"proposed":[65,89],"method":[66],"simultaneously":[67],"estimates":[68],"clean":[70],"image":[72],"sparse":[74],"solving":[77],"convex":[79],"optimization":[80],"problem.":[81],"Experimental":[82],"results":[83],"illustrate":[84],"utility":[86],"framework.":[90]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}