{"id":"https://openalex.org/W2754036486","doi":"https://doi.org/10.1142/s0219691317500643","title":"Destriping hyperspectral imagery via spectral\u2013spatial low-rank representation","display_name":"Destriping hyperspectral imagery via spectral\u2013spatial low-rank representation","publication_year":2017,"publication_date":"2017-09-19","ids":{"openalex":"https://openalex.org/W2754036486","doi":"https://doi.org/10.1142/s0219691317500643","mag":"2754036486"},"language":"en","primary_location":{"id":"doi:10.1142/s0219691317500643","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219691317500643","pdf_url":null,"source":{"id":"https://openalex.org/S56986848","display_name":"International Journal of Wavelets Multiresolution and Information Processing","issn_l":"0219-6913","issn":["0219-6913","1793-690X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wavelets, Multiresolution and Information Processing","raw_type":"journal-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/A5100449192","display_name":"Yulong Wang","orcid":"https://orcid.org/0000-0001-8148-3099"},"institutions":[{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yulong Wang","raw_affiliation_strings":["School of Information Science and Engineering, Chengdu University, Chengdu 610106, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Chengdu University, Chengdu 610106, P. R. China","institution_ids":["https://openalex.org/I4210125143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047734953","display_name":"Cuiming Zou","orcid":"https://orcid.org/0000-0002-2283-9048"},"institutions":[{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cuiming Zou","raw_affiliation_strings":["School of Information Science and Engineering, Chengdu University, Chengdu 610106, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Chengdu University, Chengdu 610106, P. R. China","institution_ids":["https://openalex.org/I4210125143"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100449192"],"corresponding_institution_ids":["https://openalex.org/I4210125143"],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46500377,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"15","issue":"06","first_page":"1750064","last_page":"1750064"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9997000098228455,"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":0.9997000098228455,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994000196456909,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9988999962806702,"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":0.9287468194961548},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6879429221153259},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.6307031512260437},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.6276010870933533},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5305201411247253},{"id":"https://openalex.org/keywords/data-striping","display_name":"Data striping","score":0.5076814889907837},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4848848283290863},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.43906399607658386},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.42627495527267456},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4248754382133484},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3520227372646332},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.31509000062942505},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1378682255744934},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.10006284713745117},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09424763917922974}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9287468194961548},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6879429221153259},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.6307031512260437},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.6276010870933533},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5305201411247253},{"id":"https://openalex.org/C83489325","wikidata":"https://www.wikidata.org/wiki/Q1332256","display_name":"Data striping","level":2,"score":0.5076814889907837},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4848848283290863},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.43906399607658386},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.42627495527267456},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4248754382133484},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3520227372646332},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31509000062942505},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1378682255744934},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.10006284713745117},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09424763917922974},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0219691317500643","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219691317500643","pdf_url":null,"source":{"id":"https://openalex.org/S56986848","display_name":"International Journal of Wavelets Multiresolution and Information Processing","issn_l":"0219-6913","issn":["0219-6913","1793-690X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wavelets, Multiresolution and Information Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4000000059604645,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1488409280","https://openalex.org/W1965051846","https://openalex.org/W1968926700","https://openalex.org/W1977527736","https://openalex.org/W1997201895","https://openalex.org/W2034671455","https://openalex.org/W2039596145","https://openalex.org/W2055678260","https://openalex.org/W2058453009","https://openalex.org/W2073797589","https://openalex.org/W2094487168","https://openalex.org/W2101815616","https://openalex.org/W2103056131","https://openalex.org/W2103972604","https://openalex.org/W2107799335","https://openalex.org/W2123180320","https://openalex.org/W2125331746","https://openalex.org/W2127141393","https://openalex.org/W2130132923","https://openalex.org/W2131697388","https://openalex.org/W2136604679","https://openalex.org/W2146127732","https://openalex.org/W2156366154","https://openalex.org/W2158400785","https://openalex.org/W2252235258","https://openalex.org/W2513407447","https://openalex.org/W4292363360"],"related_works":["https://openalex.org/W2497716132","https://openalex.org/W4298083557","https://openalex.org/W1687767907","https://openalex.org/W646673227","https://openalex.org/W1505557344","https://openalex.org/W193306665","https://openalex.org/W594670093","https://openalex.org/W604680030","https://openalex.org/W2128563350","https://openalex.org/W596844122"],"abstract_inverted_index":{"In":[0,109],"this":[1,16],"paper,":[2],"we":[3,18,55,75,97,111],"address":[4],"the":[5,28,34,50,61,69,77,86,93,99,120,131,134],"problem":[6],"of":[7,27,33,53,64,89,133,139],"removing":[8],"striping":[9,94],"noise":[10],"in":[11],"hyperspectral":[12,35],"images":[13],"(HSI).":[14],"To":[15,38,48,67],"end,":[17],"develop":[19],"a":[20,105],"novel":[21],"destriping":[22,138],"method":[23],"by":[24],"taking":[25],"advantage":[26],"spectral":[29,51,100],"and":[30,101],"spatial":[31,70,102],"information":[32,52,71,88],"image":[36],"simultaneously.":[37],"obtain":[39],"satisfactory":[40],"destriped":[41],"results,":[42],"our":[43,73],"consideration":[44],"is":[45],"two-fold:":[46],"(1)":[47],"model":[49,83,103],"HSI,":[54],"utilize":[56],"low-rank":[57,62],"representation":[58],"to":[59,84,118],"exploit":[60],"property":[63],"HSI;":[65],"(2)":[66],"incorporate":[68],"into":[72,104],"method,":[74],"adopt":[76],"Huber-Markov":[78],"random":[79],"field":[80],"(HMRF)":[81],"prior":[82],"preserve":[85],"edge":[87],"HSI":[90,128],"while":[91],"reducing":[92],"noise.":[95],"Finally,":[96],"integrate":[98],"unified":[106],"objective":[107,121],"function.":[108,122],"addition,":[110],"also":[112],"devise":[113],"an":[114],"effective":[115],"optimization":[116],"algorithm":[117],"minimize":[119],"The":[123],"experimental":[124],"results":[125],"on":[126],"real-world":[127],"data":[129],"validate":[130],"efficacy":[132],"proposed":[135],"scheme":[136],"for":[137],"HSI.":[140]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
