{"id":"https://openalex.org/W2547534670","doi":"https://doi.org/10.3390/rs8110919","title":"A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images","display_name":"A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images","publication_year":2016,"publication_date":"2016-11-05","ids":{"openalex":"https://openalex.org/W2547534670","doi":"https://doi.org/10.3390/rs8110919","mag":"2547534670"},"language":"en","primary_location":{"id":"doi:10.3390/rs8110919","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs8110919","pdf_url":"https://www.mdpi.com/2072-4292/8/11/919/pdf?version=1478331175","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/8/11/919/pdf?version=1478331175","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100364886","display_name":"Yi Wang","orcid":"https://orcid.org/0000-0002-1347-7030"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Wang","raw_affiliation_strings":["Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China"],"affiliations":[{"raw_affiliation_string":"Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100456408","display_name":"Yan Zhang","orcid":"https://orcid.org/0000-0003-2961-2396"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Zhang","raw_affiliation_strings":["Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China"],"affiliations":[{"raw_affiliation_string":"Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069053869","display_name":"Haiwei Song","orcid":"https://orcid.org/0000-0001-6398-9280"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiwei Song","raw_affiliation_strings":["Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China"],"affiliations":[{"raw_affiliation_string":"Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100364886"],"corresponding_institution_ids":["https://openalex.org/I3124059619"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.964,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.894796,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"8","issue":"11","first_page":"919","last_page":"919"},"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":0.9959999918937683,"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":0.9643999934196472,"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":0.8018788695335388},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7659443616867065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7248122692108154},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5643590092658997},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5433633327484131},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4969315826892853},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.45242205262184143},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.44409313797950745},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3974698781967163},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2563748359680176}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8018788695335388},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7659443616867065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7248122692108154},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5643590092658997},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5433633327484131},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4969315826892853},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.45242205262184143},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.44409313797950745},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3974698781967163},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2563748359680176},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs8110919","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs8110919","pdf_url":"https://www.mdpi.com/2072-4292/8/11/919/pdf?version=1478331175","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2b1ba81b74394c3d95fc7b3e2f944544","is_oa":true,"landing_page_url":"https://doaj.org/article/2b1ba81b74394c3d95fc7b3e2f944544","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 8, Iss 11, p 919 (2016)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs8110919","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs8110919","pdf_url":"https://www.mdpi.com/2072-4292/8/11/919/pdf?version=1478331175","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2174087448","display_name":null,"funder_award_id":"61271408","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309036","display_name":"Purdue University","ror":"https://ror.org/02dqehb95"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322874","display_name":"Universit\u00e0 degli Studi di Pavia","ror":"https://ror.org/00s6t1f81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2547534670.pdf","grobid_xml":"https://content.openalex.org/works/W2547534670.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W59495185","https://openalex.org/W628438000","https://openalex.org/W1510526001","https://openalex.org/W1560724230","https://openalex.org/W1972524915","https://openalex.org/W1972679354","https://openalex.org/W1976615758","https://openalex.org/W1977608287","https://openalex.org/W2001298023","https://openalex.org/W2008847349","https://openalex.org/W2011745746","https://openalex.org/W2016819955","https://openalex.org/W2016860790","https://openalex.org/W2053852479","https://openalex.org/W2054611379","https://openalex.org/W2055702796","https://openalex.org/W2057540576","https://openalex.org/W2059089906","https://openalex.org/W2067532478","https://openalex.org/W2079502224","https://openalex.org/W2085529604","https://openalex.org/W2092071303","https://openalex.org/W2095190520","https://openalex.org/W2098057602","https://openalex.org/W2101365302","https://openalex.org/W2101711129","https://openalex.org/W2103568877","https://openalex.org/W2104269704","https://openalex.org/W2105386417","https://openalex.org/W2107968230","https://openalex.org/W2114407479","https://openalex.org/W2114819256","https://openalex.org/W2124571274","https://openalex.org/W2128873066","https://openalex.org/W2129652905","https://openalex.org/W2131697388","https://openalex.org/W2135431554","https://openalex.org/W2136251662","https://openalex.org/W2149471024","https://openalex.org/W2153409933","https://openalex.org/W2153635508","https://openalex.org/W2154874087","https://openalex.org/W2156438113","https://openalex.org/W2158400785","https://openalex.org/W2159070926","https://openalex.org/W2160662337","https://openalex.org/W2164330327","https://openalex.org/W2165771856","https://openalex.org/W2166923144","https://openalex.org/W2325569213","https://openalex.org/W2478493250","https://openalex.org/W2508058002","https://openalex.org/W2518759513","https://openalex.org/W6630424276","https://openalex.org/W7010180456"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440"],"abstract_inverted_index":{"Classification":[0],"of":[1,68,114,137,166,226,236,247],"hyperspectral":[2,41,52,193,248],"images":[3,42,249],"always":[4],"suffers":[5],"from":[6,219],"high":[7],"dimensionality":[8],"and":[9,22,28,157,254],"very":[10,208],"limited":[11,209],"labeled":[12],"samples.":[13],"Recently,":[14],"the":[15,54,64,69,80,87,100,120,126,135,141,155,158,163,167,171,177,184,230],"spectral-spatial":[16,37],"classification":[17,26,30,38,138,172,202,245],"has":[18],"attracted":[19],"considerable":[20],"attention":[21],"can":[23,132,199,217],"achieve":[24,218],"higher":[25,223],"accuracy":[27,228],"smoother":[29],"maps.":[31],"In":[32,140],"this":[33,105],"paper,":[34],"a":[35,50,116,144,207,255],"novel":[36],"method":[39,198,216,238],"for":[40],"by":[43,78,150,176],"using":[44,79,162,183,250],"kernel":[45,147,168],"methods":[46,246],"is":[47,60,72,92,107,148,174,212],"investigated.":[48],"For":[49],"given":[51],"image,":[53],"principle":[55,66],"component":[56,67],"analysis":[57],"(PCA)":[58],"transform":[59],"first":[61,65],"performed.":[62],"Then,":[63],"input":[70],"image":[71,118,127,156],"segmented":[73],"into":[74],"non-overlapping":[75],"homogeneous":[76,96],"regions":[77],"entropy":[81],"rate":[82],"superpixel":[83],"(ERS)":[84],"algorithm.":[85],"Next,":[86],"local":[88,122],"spectral":[89,152],"histogram":[90],"model":[91],"applied":[93],"to":[94,98,221,242],"each":[95,110],"region":[97],"obtain":[99],"corresponding":[101],"texture":[102,123,160],"features.":[103],"Because":[104],"step":[106],"performed":[108],"within":[109,115],"homogenous":[111],"region,":[112],"instead":[113],"fixed-size":[117],"window,":[119],"obtained":[121],"features":[124],"in":[125,154,224],"are":[128],"more":[129],"accurate,":[130],"which":[131],"effectively":[133,200],"benefit":[134],"improvement":[136],"accuracy.":[139],"following":[142],"step,":[143],"contextual":[145],"spectral-texture":[146,186],"constructed":[149],"combining":[151],"information":[153,161],"extracted":[159],"linearity":[164],"property":[165],"methods.":[169],"Finally,":[170],"map":[173],"achieved":[175],"support":[178],"vector":[179],"machines":[180],"(SVM)":[181],"classifier":[182],"proposed":[185],"kernel.":[187],"Experiments":[188],"on":[189],"two":[190],"benchmark":[191],"airborne":[192],"datasets":[194],"demonstrate":[195],"that":[196],"our":[197,215,237],"improve":[201],"accuracies,":[203],"even":[204],"though":[205],"only":[206],"training":[210],"sample":[211],"available.":[213],"Specifically,":[214],"8.26%":[220],"15.1%":[222],"terms":[225],"overall":[227],"than":[229],"traditional":[231],"SVM":[232],"classifier.":[233],"The":[234],"performance":[235],"was":[239],"further":[240],"compared":[241],"several":[243],"state-of-the-art":[244],"objective":[251],"quantitative":[252],"measures":[253],"visual":[256],"qualitative":[257],"evaluation.":[258]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}
