{"id":"https://openalex.org/W2937817153","doi":"https://doi.org/10.1109/icassp.2019.8683646","title":"Hyperspectral and Multispectral Data Fusion by a Regularization Considering","display_name":"Hyperspectral and Multispectral Data Fusion by a Regularization Considering","publication_year":2019,"publication_date":"2019-04-17","ids":{"openalex":"https://openalex.org/W2937817153","doi":"https://doi.org/10.1109/icassp.2019.8683646","mag":"2937817153"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8683646","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683646","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"middle","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"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024015306","display_name":"Itsuo Kumazawa","orcid":"https://orcid.org/0000-0002-5409-2727"},"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":"Itsuo Kumazawa","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":3,"corresponding_author_ids":["https://openalex.org/A5073256619"],"corresponding_institution_ids":["https://openalex.org/I114531698"],"apc_list":null,"apc_paid":null,"fwci":0.8927,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.77653373,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2152","last_page":"2156"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9957000017166138,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.886069655418396},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.8859783411026001},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.6775800585746765},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6039412021636963},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5660567283630371},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.538852870464325},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4920365512371063},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4878654479980469},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39138051867485046},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.16377049684524536}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.886069655418396},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.8859783411026001},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6775800585746765},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6039412021636963},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5660567283630371},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.538852870464325},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4920365512371063},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4878654479980469},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39138051867485046},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.16377049684524536},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2019.8683646","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683646","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W54434497","https://openalex.org/W205960364","https://openalex.org/W1532610010","https://openalex.org/W1667895010","https://openalex.org/W1940108662","https://openalex.org/W1990231296","https://openalex.org/W2021046129","https://openalex.org/W2039596145","https://openalex.org/W2041320831","https://openalex.org/W2092663520","https://openalex.org/W2123031198","https://openalex.org/W2124743705","https://openalex.org/W2131697388","https://openalex.org/W2142843085","https://openalex.org/W2171108951","https://openalex.org/W2221899823","https://openalex.org/W2563625031","https://openalex.org/W2578004414","https://openalex.org/W2594827121","https://openalex.org/W2606306511","https://openalex.org/W2625894731","https://openalex.org/W2628535015","https://openalex.org/W2765202580","https://openalex.org/W3016867217","https://openalex.org/W3099843321","https://openalex.org/W3102912004","https://openalex.org/W3106359998","https://openalex.org/W4229650096","https://openalex.org/W6602248423","https://openalex.org/W6735339649","https://openalex.org/W6745193812","https://openalex.org/W6776415401"],"related_works":["https://openalex.org/W2022304901","https://openalex.org/W2018850895","https://openalex.org/W2988577871","https://openalex.org/W1987483041","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2353265673","https://openalex.org/W2031175860","https://openalex.org/W2152662039"],"abstract_inverted_index":{"A":[0],"hyperspectral":[1],"(HS)":[2],"image":[3,18,37,57,103,140,150,165,196],"has":[4],"high":[5,20,42,61],"spectral":[6,23,43,62,111],"resolution":[7,12,24,44,65],"information":[8,66],"but":[9,151],"low":[10,39],"spatial":[11,21,40,64],"information.":[13],"To":[14,113],"get":[15],"an":[16,35,100],"HS":[17,26,36,56,68,84,121,139,149,164],"of":[19,38,67,182,192],"and":[22,41,45,63,69,85,89,110,122,189],"(high-spatial":[25],"image),":[27],"fusion":[28,125,187],"techniques":[29,51],"are":[30,171],"actively":[31],"studied,":[32],"which":[33,134],"synthesize":[34],"a":[46,54,97,119,128,136,147,154,162],"multispectral":[47],"(MS)":[48],"image.":[49,95],"The":[50,142],"can":[52],"generate":[53],"high-spatial":[55,148,163],"by":[58,173],"exploiting":[59],"the":[60,74,79,93,168,176,180,190],"MS":[70,87,94,102,123,156,195],"images,":[71,88],"respectively.":[72],"However,":[73],"methods":[75,107,188],"do":[76,90],"not":[77,91,144],"evaluate":[78],"edge":[80],"similarity":[81],"between":[82],"generated":[83],"observed":[86,101,169],"denoise":[92],"As":[96],"result,":[98],"when":[99],"is":[104,135],"noisy,":[105],"these":[106],"produce":[108],"artifacts":[109],"distortion.":[112],"tackle":[114],"this":[115],"problem,":[116],"we":[117,160,178],"propose":[118],"new":[120],"data":[124],"method":[126,143,184],"using":[127],"hybrid":[129],"spatio-spectral":[130],"total":[131],"variation":[132],"(HSSTV),":[133],"regularization":[137],"for":[138,194],"restoration.":[141,197],"only":[145],"generates":[146],"also":[152],"denoises":[153],"given":[155],"image,":[157],"so":[158],"that":[159],"obtain":[161],"even":[166],"if":[167],"images":[170],"contaminated":[172],"noise.":[174],"In":[175],"experiments,":[177],"demonstrate":[179],"advantages":[181],"our":[183],"over":[185],"existing":[186],"effectiveness":[191],"HSSTV":[193]},"counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}