{"id":"https://openalex.org/W3112261204","doi":"https://doi.org/10.3390/rs12233967","title":"An Efficient Spectral Feature Extraction Framework for Hyperspectral Images","display_name":"An Efficient Spectral Feature Extraction Framework for Hyperspectral Images","publication_year":2020,"publication_date":"2020-12-04","ids":{"openalex":"https://openalex.org/W3112261204","doi":"https://doi.org/10.3390/rs12233967","mag":"3112261204"},"language":"en","primary_location":{"id":"doi:10.3390/rs12233967","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12233967","pdf_url":null,"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://doi.org/10.3390/rs12233967","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100681000","display_name":"Zhen Li","orcid":"https://orcid.org/0000-0002-2049-2108"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Li","raw_affiliation_strings":["Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China"],"raw_orcid":"https://orcid.org/0000-0002-2049-2108","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100985496","display_name":"Baojun Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baojun Zhao","raw_affiliation_strings":["Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049895843","display_name":"Wenzheng Wang","orcid":"https://orcid.org/0000-0002-0278-6751"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenzheng Wang","raw_affiliation_strings":["Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China","School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5049895843"],"corresponding_institution_ids":["https://openalex.org/I125839683","https://openalex.org/I20231570"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.1475,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.84667789,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"12","issue":"23","first_page":"3967","last_page":"3967"},"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":0.9692000150680542,"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/T10057","display_name":"Face and Expression Recognition","score":0.963699996471405,"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/discriminative-model","display_name":"Discriminative model","score":0.8832781314849854},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8742696046829224},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7961117029190063},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6871473789215088},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6707215905189514},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5606043338775635},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5374159812927246},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5112054347991943},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4367482662200928},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4347556233406067},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.43283113837242126},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4125770926475525},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13990694284439087},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11408156156539917}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8832781314849854},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8742696046829224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7961117029190063},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6871473789215088},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6707215905189514},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5606043338775635},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5374159812927246},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5112054347991943},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4367482662200928},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4347556233406067},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.43283113837242126},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4125770926475525},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13990694284439087},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11408156156539917},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs12233967","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12233967","pdf_url":null,"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:ae8c4f87dfab4617b5af3a4bb533d62f","is_oa":true,"landing_page_url":"https://doaj.org/article/ae8c4f87dfab4617b5af3a4bb533d62f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"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 12, Iss 23, p 3967 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/23/3967/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12233967","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 12; Issue 23; Pages: 3967","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12233967","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12233967","pdf_url":null,"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":[{"display_name":"Reduced inequalities","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G227357655","display_name":null,"funder_award_id":"91438203,31727901","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1560724230","https://openalex.org/W1997565609","https://openalex.org/W2009951413","https://openalex.org/W2027805700","https://openalex.org/W2028623420","https://openalex.org/W2029316659","https://openalex.org/W2032768707","https://openalex.org/W2041100636","https://openalex.org/W2047705660","https://openalex.org/W2054502547","https://openalex.org/W2067983477","https://openalex.org/W2069231830","https://openalex.org/W2090424610","https://openalex.org/W2097915756","https://openalex.org/W2104269704","https://openalex.org/W2111072639","https://openalex.org/W2129812935","https://openalex.org/W2132467081","https://openalex.org/W2141695047","https://openalex.org/W2142012908","https://openalex.org/W2157785665","https://openalex.org/W2164278908","https://openalex.org/W2166371785","https://openalex.org/W2169073444","https://openalex.org/W2179290474","https://openalex.org/W2184852195","https://openalex.org/W2314785379","https://openalex.org/W2323917763","https://openalex.org/W2335197470","https://openalex.org/W2341545927","https://openalex.org/W2431005319","https://openalex.org/W2500751094","https://openalex.org/W2548791488","https://openalex.org/W2554764988","https://openalex.org/W2609880332","https://openalex.org/W2745252301","https://openalex.org/W2773102504","https://openalex.org/W2790473231","https://openalex.org/W2912520022","https://openalex.org/W2939570633","https://openalex.org/W2942170965","https://openalex.org/W2957321156","https://openalex.org/W2967403871","https://openalex.org/W3037490781","https://openalex.org/W3046027728","https://openalex.org/W3085534640","https://openalex.org/W3093861846","https://openalex.org/W3101640299","https://openalex.org/W3122774149","https://openalex.org/W4240485910","https://openalex.org/W4292363360","https://openalex.org/W6684213969","https://openalex.org/W6704443453"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2060875994","https://openalex.org/W2027399350","https://openalex.org/W2044184146","https://openalex.org/W2468279273","https://openalex.org/W2952115151"],"abstract_inverted_index":{"Extracting":[0],"diverse":[1,154],"spectral":[2,60,100,113,118],"features":[3,131],"from":[4,27],"hyperspectral":[5,51],"images":[6],"has":[7],"become":[8],"a":[9,28,55,82],"hot":[10],"topic":[11],"in":[12,33],"recent":[13],"years.":[14],"However,":[15],"these":[16],"models":[17],"are":[18],"time":[19],"consuming":[20],"for":[21,47,125],"training":[22,72,169],"and":[23,25,62,73,89,139,142,170],"test":[24],"suffer":[26],"poor":[29],"discriminative":[30,105,141],"ability,":[31],"resulting":[32],"low":[34],"classification":[35],"accuracy.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40,110,121],"design":[41,122],"an":[42,90],"effective":[43],"feature":[44,160],"extracting":[45],"framework":[46,162],"the":[48,76,87,99,104,129,140,158,168],"spectra":[49],"of":[50,107,132,145],"data.":[52],"We":[53],"construct":[54],"structured":[56],"dictionary":[57,146],"to":[58,66,85,97,115,176],"encode":[59],"information":[61],"apply":[63],"learning":[64,93,184],"machine":[65,94],"map":[67],"coding":[68],"coefficients.":[69],"To":[70,102],"reduce":[71,167],"testing":[74,171],"time,":[75,172],"sparsity":[77],"constraint":[78,84],"is":[79,95],"replaced":[80],"by":[81],"block-diagonal":[83],"accelerate":[86],"iteration,":[88],"efficient":[91],"extreme":[92],"employed":[96],"fit":[98],"characteristics.":[101],"optimize":[103],"ability":[106,144],"our":[108],"model,":[109],"first":[111],"add":[112],"convolution":[114],"extract":[116],"abundant":[117],"information.":[119],"Then,":[120],"shared":[123],"constraints":[124],"subdictionaries":[126,133],"so":[127],"that":[128,157],"common":[130],"can":[134,163],"be":[135,148],"expressed":[136],"more":[137],"effectively,":[138],"reconstructive":[143],"will":[147],"improved.":[149],"The":[150],"experimental":[151],"results":[152],"on":[153],"databases":[155],"show":[156],"proposed":[159],"extraction":[161],"not":[164],"only":[165],"greatly":[166],"but":[173],"also":[174],"lead":[175],"very":[177],"competitive":[178],"accuracy":[179],"performance":[180],"compared":[181],"with":[182],"deep":[183],"models.":[185]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}