{"id":"https://openalex.org/W2766596370","doi":"https://doi.org/10.23919/eusipco.2017.8081465","title":"Frequency spectrum regularization for pattern noise removal based on image decomposition","display_name":"Frequency spectrum regularization for pattern noise removal based on image decomposition","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2766596370","doi":"https://doi.org/10.23919/eusipco.2017.8081465","mag":"2766596370"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2017.8081465","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2017.8081465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th European Signal Processing Conference (EUSIPCO)","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/A5102792149","display_name":"Keiichiro Shirai","orcid":"https://orcid.org/0000-0003-2072-5087"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Keiichiro Shirai","raw_affiliation_strings":["Shinshu Univ"],"affiliations":[{"raw_affiliation_string":"Shinshu Univ","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040341698","display_name":"Shunsuke Ono","orcid":"https://orcid.org/0000-0001-7890-5131"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shunsuke Ono","raw_affiliation_strings":["Tokyo Institute of Tech"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Tech","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025207272","display_name":"Masahiro Okuda","orcid":"https://orcid.org/0000-0002-3245-2672"},"institutions":[{"id":"https://openalex.org/I17056963","display_name":"The University of Kitakyushu","ror":"https://ror.org/03mfefw72","country_code":"JP","type":"education","lineage":["https://openalex.org/I17056963"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahiro Okuda","raw_affiliation_strings":["Univ. of Kitakyushu"],"affiliations":[{"raw_affiliation_string":"Univ. of Kitakyushu","institution_ids":["https://openalex.org/I17056963"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102792149"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15401436,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1529","last_page":"1533"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998999834060669,"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":0.9998999834060669,"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/T11105","display_name":"Advanced Image Processing 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"}}],"keywords":[{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5469775199890137},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.49458834528923035},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4726221561431885},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.47213298082351685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4455453157424927},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4420930743217468},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.434895783662796},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4315018355846405},{"id":"https://openalex.org/keywords/frequency-band","display_name":"Frequency band","score":0.42086735367774963},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41622859239578247},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39360830187797546},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.33111196756362915},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.303134560585022},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.10131001472473145},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.0779697597026825}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5469775199890137},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.49458834528923035},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4726221561431885},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.47213298082351685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4455453157424927},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4420930743217468},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.434895783662796},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4315018355846405},{"id":"https://openalex.org/C2778116611","wikidata":"https://www.wikidata.org/wiki/Q25110567","display_name":"Frequency band","level":3,"score":0.42086735367774963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41622859239578247},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39360830187797546},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33111196756362915},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.303134560585022},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.10131001472473145},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0779697597026825},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2017.8081465","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2017.8081465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1972568768","https://openalex.org/W1980212291","https://openalex.org/W2004346156","https://openalex.org/W2007927352","https://openalex.org/W2045079045","https://openalex.org/W2054110507","https://openalex.org/W2073704304","https://openalex.org/W2085411553","https://openalex.org/W2103559027","https://openalex.org/W2131628350","https://openalex.org/W2164278908","https://openalex.org/W2280409827","https://openalex.org/W3099931851","https://openalex.org/W4292363360"],"related_works":["https://openalex.org/W2380059383","https://openalex.org/W2063679720","https://openalex.org/W2067481825","https://openalex.org/W2075046161","https://openalex.org/W2185495545","https://openalex.org/W2547083368","https://openalex.org/W2031856784","https://openalex.org/W2510721029","https://openalex.org/W2385335131","https://openalex.org/W239705756"],"abstract_inverted_index":{"This":[0,105],"paper":[1],"deals":[2],"with":[3,45],"a":[4,82,87,107,126],"mixed":[5,24],"norm":[6,25],"of":[7,13,22,36,52,67,81,110],"complex":[8],"vectors,":[9],"i.e.,":[10],"the":[11,49,96,101,111],"sum":[12],"amplitude":[14],"spectra,":[15],"and":[16,26,34,86,91,100,133],"its":[17],"minimization":[18],"problem.":[19],"A":[20],"combination":[21],"this":[23,131],"image":[27,79,84],"decomposition":[28,35,109,117,128],"problem":[29],"works":[30],"well":[31],"for":[32,130],"reduction":[33],"pattern":[37,68,88],"noise":[38,69,89],"that":[39,66,76],"arises":[40],"when":[41],"scanning":[42],"old":[43],"photographs":[44],"granulated":[46],"surface.":[47],"Generally,":[48],"spectral":[50],"distribution":[51],"natural":[53],"images":[54],"decreases":[55],"smoothly":[56],"from":[57],"low":[58,134],"frequency":[59,63],"band":[60],"toward":[61],"high":[62],"band,":[64],"while":[65],"is":[70],"distributed":[71],"sparsely.":[72],"Therefore,":[73],"we":[74],"assume":[75],"an":[77],"observed":[78],"consists":[80],"latent":[83],"component":[85],"component,":[90],"characterize":[92],"them":[93],"by":[94],"using":[95],"total":[97],"variation":[98],"function":[99],"proposed":[102],"function,":[103],"respectively.":[104],"enables":[106],"reasonable":[108],"two":[112],"components.":[113],"Compared":[114],"to":[115],"similar":[116],"methods":[118],"such":[119],"as":[120],"Robust":[121],"PCA,":[122],"our":[123],"method":[124],"has":[125],"good":[127],"accuracy":[129],"task,":[132],"computational":[135],"cost.":[136]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
