{"id":"https://openalex.org/W2972485657","doi":"https://doi.org/10.1109/i2mtc.2019.8827111","title":"Superpixel-based HSI Classification via Semisupervised K-SVD and Multi-scale Sparse Representation","display_name":"Superpixel-based HSI Classification via Semisupervised K-SVD and Multi-scale Sparse Representation","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2972485657","doi":"https://doi.org/10.1109/i2mtc.2019.8827111","mag":"2972485657"},"language":"en","primary_location":{"id":"doi:10.1109/i2mtc.2019.8827111","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc.2019.8827111","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","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/A5101811922","display_name":"Lianlei Lin","orcid":"https://orcid.org/0000-0001-6829-5747"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lianlei Lin","raw_affiliation_strings":["Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071277982","display_name":"Cailu Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cailu Chen","raw_affiliation_strings":["Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007025260","display_name":"Zhuxu Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuxu Zhou","raw_affiliation_strings":["Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100412117","display_name":"Shanshan Zhang","orcid":"https://orcid.org/0000-0002-1055-2162"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanshan Zhang","raw_affiliation_strings":["Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101811922"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":0.1785,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55681884,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"27","issue":null,"first_page":"1","last_page":"6"},"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/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"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9945999979972839,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.799919605255127},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7785922288894653},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.697393000125885},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6917343139648438},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.6826547384262085},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.6768024563789368},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6069976687431335},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5253462195396423},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4146340489387512},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41355857253074646},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36699020862579346}],"concepts":[{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.799919605255127},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7785922288894653},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.697393000125885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6917343139648438},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.6826547384262085},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.6768024563789368},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6069976687431335},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5253462195396423},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4146340489387512},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41355857253074646},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36699020862579346},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/i2mtc.2019.8827111","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc.2019.8827111","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1808881044","https://openalex.org/W1972814520","https://openalex.org/W1974774078","https://openalex.org/W1976709621","https://openalex.org/W1998030734","https://openalex.org/W1998902551","https://openalex.org/W2001298023","https://openalex.org/W2015380729","https://openalex.org/W2030965277","https://openalex.org/W2052160904","https://openalex.org/W2074054045","https://openalex.org/W2097915756","https://openalex.org/W2101365302","https://openalex.org/W2104125540","https://openalex.org/W2105386417","https://openalex.org/W2113464037","https://openalex.org/W2131697388","https://openalex.org/W2134930443","https://openalex.org/W2136251662","https://openalex.org/W2142012908","https://openalex.org/W2145889472","https://openalex.org/W2153663612","https://openalex.org/W2158400785","https://openalex.org/W2160547390","https://openalex.org/W2164330327","https://openalex.org/W2164437025","https://openalex.org/W2165049595","https://openalex.org/W2898342702","https://openalex.org/W4292915233","https://openalex.org/W6650037220"],"related_works":["https://openalex.org/W1971373099","https://openalex.org/W2099321050","https://openalex.org/W2890952311","https://openalex.org/W2374021060","https://openalex.org/W2509955295","https://openalex.org/W2047275718","https://openalex.org/W2034957211","https://openalex.org/W2388952560","https://openalex.org/W110819671","https://openalex.org/W2532569109"],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1,33],"(HSI)":[2],"classification":[3,34,121],"is":[4,24,44,50,60,70,123,143],"one":[5],"of":[6,78,135],"the":[7,54,57,76,85,92,96,126,133,136],"most":[8],"important":[9],"techniques":[10],"in":[11,95,105],"HSI-based":[12],"measurement.":[13],"In":[14],"this":[15],"paper,":[16],"a":[17,30,116],"semi-supervised":[18,37,48],"k-singular":[19],"value":[20],"decomposition":[21],"(K-SVD)":[22],"algorithm":[23,59,122,138],"proposed,":[25],"and":[26,39,68,83,112],"based":[27],"on":[28,130],"this,":[29],"superpixel-based":[31],"hyperspectral":[32],"method":[35],"combining":[36],"K-SVD":[38,49,58],"multi-scale":[40,117],"sparse":[41,87,93,118],"representation":[42,119],"(SK-MSR)":[43],"further":[45],"proposed.":[46,124],"The":[47],"proposed":[51],"to":[52,90,107,140],"solve":[53,91],"problems":[55],"that":[56],"not":[61],"good":[62],"at":[63],"processing":[64],"small":[65],"sample":[66],"signals":[67],"there":[69],"no":[71],"class":[72],"distinction,":[73],"which":[74],"expands":[75],"number":[77],"training":[79],"samples":[80],"by":[81],"superpixels":[82],"uses":[84],"joint":[86],"model":[88],"(JSM)":[89],"problem":[94],"dictionary":[97],"learning":[98],"process.":[99],"After":[100],"obtaining":[101],"an":[102],"over-complete":[103],"dictionary,":[104],"order":[106],"effectively":[108],"use":[109],"spatial":[110],"information":[111],"remove":[113],"salt-and-pepper":[114],"noise,":[115],"superpixel":[120],"Through":[125],"performance":[127],"comparison":[128],"experiments":[129],"two":[131],"datasets,":[132],"superiority":[134],"SK-MSR":[137],"relative":[139],"other":[141],"algorithms":[142],"demonstrated.":[144]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}