{"id":"https://openalex.org/W2970683532","doi":"https://doi.org/10.1109/icip.2019.8803239","title":"Mixed Noise Removal for Hyperspectral Images Using Hybrid Spatio-Spectral Total Variation","display_name":"Mixed Noise Removal for Hyperspectral Images Using Hybrid Spatio-Spectral Total Variation","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2970683532","doi":"https://doi.org/10.1109/icip.2019.8803239","mag":"2970683532"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","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, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Tokyo, Japan","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, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Tokyo, Japan","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, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Tokyo, Japan","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":0.911,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.79202607,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"3","issue":null,"first_page":"3128","last_page":"3132"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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"}},"topics":[{"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9995999932289124,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9995999932289124,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7360431551933289},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.6656618714332581},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6149329543113708},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6098259687423706},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.536255955696106},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5323296785354614},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.5068338513374329},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.48022159934043884},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4301249384880066},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4193882942199707},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3888011574745178},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3833831548690796},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33220165967941284},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33194634318351746},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2463667094707489}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7360431551933289},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.6656618714332581},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6149329543113708},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6098259687423706},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.536255955696106},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5323296785354614},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.5068338513374329},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.48022159934043884},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4301249384880066},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4193882942199707},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3888011574745178},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3833831548690796},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33220165967941284},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33194634318351746},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2463667094707489},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2019.8803239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1532610010","https://openalex.org/W1667895010","https://openalex.org/W1944540851","https://openalex.org/W1978259121","https://openalex.org/W2014823423","https://openalex.org/W2039596145","https://openalex.org/W2045079045","https://openalex.org/W2058532290","https://openalex.org/W2123031198","https://openalex.org/W2131697388","https://openalex.org/W2145962650","https://openalex.org/W2164278908","https://openalex.org/W2289756263","https://openalex.org/W2336406062","https://openalex.org/W2578004414","https://openalex.org/W2594827121","https://openalex.org/W2628535015","https://openalex.org/W2765202580","https://openalex.org/W2802729498","https://openalex.org/W2890107589","https://openalex.org/W2901043666","https://openalex.org/W3106359998"],"related_works":["https://openalex.org/W3211035526","https://openalex.org/W1869808405","https://openalex.org/W3173596272","https://openalex.org/W2028628118","https://openalex.org/W4291701050","https://openalex.org/W2891352623","https://openalex.org/W2972973180","https://openalex.org/W4293272463","https://openalex.org/W2397512269","https://openalex.org/W1932002646"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,10,31,92],"new":[4],"mixed":[5,39],"noise":[6,40],"removal":[7,41],"method":[8,89,108,133],"using":[9],"hybrid":[11],"spatio-spectral":[12],"total":[13],"variation":[14],"(HSSTV)":[15],"for":[16,34],"hy-perspectral":[17],"(HS)":[18],"images.":[19],"HSSTV":[20],"effectively":[21],"evaluates":[22],"spatial":[23,59],"and":[24,28,100],"spectral":[25],"piecewise":[26,60],"smoothness":[27],"would":[29],"be":[30],"powerful":[32],"regularization":[33],"HS":[35,48,94],"image":[36,49,95],"restoration.":[37],"Existing":[38],"methods":[42,72],"evaluate":[43,58],"a-priori":[44],"knowledge":[45],"of":[46,130],"an":[47],"via":[50],"multiple":[51,77],"regularizations.":[52,136],"However,":[53],"they":[54],"do":[55],"not":[56],"appropriately":[57],"smoothness,":[61],"resulting":[62],"in":[63,70,106],"oversmoothing":[64],"or":[65],"artifacts.":[66],"Moreover,":[67],"parameter":[68,104],"settings":[69,105],"existing":[71,113,135],"are":[73,80,109],"troublesome":[74],"tasks":[75],"because":[76,115],"balancing":[78],"parameters":[79],"interdependent.":[81],"In":[82,102,123],"contrast,":[83],"thanks":[84],"to":[85],"HSSTV,":[86],"the":[87,124,128],"proposed":[88,132],"can":[90],"restore":[91],"clean":[93],"while":[96],"keeping":[97],"sharp":[98],"edges":[99],"details.":[101],"addition,":[103],"our":[107,131],"much":[110],"easier":[111],"than":[112],"ones":[114],"data":[116],"fidelity":[117],"is":[118],"imposed":[119],"as":[120],"hard":[121],"constraints.":[122],"experiments,":[125],"we":[126],"demonstrate":[127],"advantages":[129],"over":[134]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"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"}
