{"id":"https://openalex.org/W2603183506","doi":"https://doi.org/10.1142/s021969131750028x","title":"Robust patch-based sparse representation for hyperspectral image classification","display_name":"Robust patch-based sparse representation for hyperspectral image classification","publication_year":2017,"publication_date":"2017-03-20","ids":{"openalex":"https://openalex.org/W2603183506","doi":"https://doi.org/10.1142/s021969131750028x","mag":"2603183506"},"language":"en","primary_location":{"id":"doi:10.1142/s021969131750028x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021969131750028x","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/A5016933731","display_name":"Haoliang Yuan","orcid":"https://orcid.org/0000-0001-5167-226X"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haoliang Yuan","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou 510006, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou 510006, P. R. China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5016933731"],"corresponding_institution_ids":["https://openalex.org/I139024713"],"apc_list":null,"apc_paid":null,"fwci":1.4125,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.8449371,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"15","issue":"03","first_page":"1750028","last_page":"1750028"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","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/T10689","display_name":"Remote-Sensing Image Classification","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/T13890","display_name":"Remote Sensing and Land Use","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9926999807357788,"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":0.7897847890853882},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.658115029335022},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.6397063732147217},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5950068235397339},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5773059129714966},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5629734992980957},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.5557606220245361},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.543716311454773},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4411930739879608},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.44097772240638733},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4107983112335205},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.1800927221775055}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7897847890853882},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.658115029335022},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.6397063732147217},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5950068235397339},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5773059129714966},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5629734992980957},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.5557606220245361},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.543716311454773},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4411930739879608},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.44097772240638733},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4107983112335205},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.1800927221775055},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s021969131750028x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021969131750028x","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":[{"display_name":"Sustainable cities and communities","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1557270207","https://openalex.org/W1633071488","https://openalex.org/W1904464160","https://openalex.org/W1948068958","https://openalex.org/W1969630109","https://openalex.org/W1997565609","https://openalex.org/W2001298023","https://openalex.org/W2031510368","https://openalex.org/W2035128422","https://openalex.org/W2048281487","https://openalex.org/W2052160904","https://openalex.org/W2079539078","https://openalex.org/W2097915756","https://openalex.org/W2104269704","https://openalex.org/W2106777458","https://openalex.org/W2129812935","https://openalex.org/W2136251662","https://openalex.org/W2153635508","https://openalex.org/W2164330327","https://openalex.org/W2166668769","https://openalex.org/W2171566342","https://openalex.org/W2237758977","https://openalex.org/W2282679489","https://openalex.org/W2325640983"],"related_works":["https://openalex.org/W2610195472","https://openalex.org/W2546645752","https://openalex.org/W2086869014","https://openalex.org/W2500072022","https://openalex.org/W1979158807","https://openalex.org/W2781549591","https://openalex.org/W2380303077","https://openalex.org/W2089381226","https://openalex.org/W4295864386","https://openalex.org/W2743193290"],"abstract_inverted_index":{"Sparse":[0],"representation":[1,131],"classification":[2,51,132],"(SRC)":[3],"has":[4],"been":[5],"successfully":[6],"applied":[7],"into":[8],"hyperspectral":[9],"image":[10,101],"(HSI).":[11],"A":[12],"test":[13,34],"sample":[14,35],"(pixel)":[15],"can":[16],"be":[17],"linearly":[18],"represented":[19,78],"by":[20,39],"a":[21,53,58,96,127],"few":[22],"training":[23,27],"samples":[24,104],"of":[25,32,73,159],"the":[26,33,40,45,50,66,70,74,84,87,91,100,103,106,119,157],"set.":[28],"The":[29],"class":[30],"label":[31],"is":[36,62,77,114,142],"then":[37],"decided":[38],"reconstruction":[41,75,88,120],"residuals.":[42,121],"To":[43],"incorporate":[44],"spatial":[46,59],"information":[47],"to":[48,64,110,117,144],"improve":[49],"performance,":[52],"patch":[54,97,107],"matrix,":[55],"which":[56,81],"includes":[57],"neighborhood":[60],"set,":[61],"used":[63],"replace":[65],"original":[67],"pixel.":[68],"Generally,":[69],"objective":[71],"function":[72],"residuals":[76,89],"as":[79],"Frobenius-norm,":[80],"actually":[82],"treats":[83],"elements":[85],"in":[86,90,99,105],"same":[92],"way.":[93],"However,":[94],"when":[95],"locates":[98],"edge,":[102],"may":[108],"belong":[109],"different":[111],"classes.":[112],"Frobenius-norm":[113],"not":[115],"suitable":[116],"compute":[118,145],"In":[122],"this":[123],"paper,":[124],"we":[125],"propose":[126],"robust":[128],"patch-based":[129],"sparse":[130],"(RPSRC)":[133],"based":[134],"on":[135,151],"[Formula:":[136],"see":[137],"text]-norm.":[138],"An":[139],"iteration":[140],"algorithm":[141],"given":[143],"RPSRC":[146],"efficiently.":[147],"Extensive":[148],"experimental":[149],"results":[150],"two":[152],"real-life":[153],"HSI":[154],"datasets":[155],"demonstrate":[156],"effectiveness":[158],"RPSRC.":[160]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}