{"id":"https://openalex.org/W2900456880","doi":"https://doi.org/10.1109/igarss.2018.8518800","title":"A Novel Spectrum Elaboration Method for Moving Targets Based on Empirical Mode Decomposition","display_name":"A Novel Spectrum Elaboration Method for Moving Targets Based on Empirical Mode Decomposition","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2900456880","doi":"https://doi.org/10.1109/igarss.2018.8518800","mag":"2900456880"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8518800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518800","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","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/A5100376455","display_name":"Miao Zhang","orcid":"https://orcid.org/0000-0001-9428-0573"},"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":"Miao Zhang","raw_affiliation_strings":["Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072014797","display_name":"Ruilin Yuan","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":"Ruilin Yuan","raw_affiliation_strings":["Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009129294","display_name":"Yi Shen","orcid":"https://orcid.org/0000-0002-3198-1927"},"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":"Yi Shen","raw_affiliation_strings":["Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13287956,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7259","last_page":"7262"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9954000115394592,"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":0.9941999912261963,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9091246128082275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6739333271980286},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.6412720680236816},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6103740930557251},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.5789759755134583},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5669888257980347},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5502748489379883},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4972575008869171},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.4679645001888275},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4216029942035675},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3542744517326355},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.273731529712677},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.14831429719924927}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9091246128082275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6739333271980286},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.6412720680236816},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6103740930557251},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.5789759755134583},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5669888257980347},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5502748489379883},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4972575008869171},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.4679645001888275},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4216029942035675},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3542744517326355},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.273731529712677},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.14831429719924927},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8518800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518800","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2016147261","https://openalex.org/W2109896502","https://openalex.org/W2312470762","https://openalex.org/W2399469309","https://openalex.org/W2622999037","https://openalex.org/W2773430115","https://openalex.org/W2775496210","https://openalex.org/W2794522503","https://openalex.org/W2794660888"],"related_works":["https://openalex.org/W2911259277","https://openalex.org/W4386427838","https://openalex.org/W2800956885","https://openalex.org/W2533019003","https://openalex.org/W1788560349","https://openalex.org/W2626158795","https://openalex.org/W2078656815","https://openalex.org/W2391021239","https://openalex.org/W2560525382","https://openalex.org/W2126575155"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,15,106],"overcome":[3],"the":[4,11,44,71,78,82,86,107,112,121],"noise":[5],"impact":[6],"of":[7,59,73,88],"hyperspectral":[8,38,60],"images":[9],"during":[10],"acquisition":[12],"process":[13],"due":[14],"target":[16],"movement":[17],"and":[18,36,98,111,127,131],"environmental":[19],"interference,":[20],"this":[21,49,67],"paper":[22],"proposes":[23],"a":[24,52,57,117],"spectrum":[25],"elaboration":[26],"method":[27,50,68,110,123],"based":[28],"on":[29],"empirical":[30],"mode":[31],"decomposition":[32],"(EMD)":[33],"for":[34,81],"visible":[35],"near-infrared":[37],"image":[39],"data.":[40],"The":[41,63],"difference":[42],"with":[43],"prior":[45],"arts":[46],"is":[47],"that":[48,66,76,92],"obtains":[51],"spectral":[53,74,89],"curve":[54],"by":[55],"processing":[56],"series":[58],"data":[61],"cubes.":[62],"experiments":[64],"show":[65],"can":[69],"obtain":[70],"vector":[72],"signature":[75],"reflects":[77],"essential":[79],"features":[80],"moving":[83],"object,":[84],"as":[85],"results":[87],"angle":[90],"indicate":[91],"discrepancies":[93],"between":[94],"non-congeners":[95],"are":[96,101],"greater":[97],"similar":[99],"congeners":[100],"more":[102],"similar,":[103],"which":[104],"compared":[105],"gaussian":[108],"filtering":[109],"direct":[113],"averaging":[114],"method.":[115],"has":[116,128],"higher":[118],"accuracy":[119],"than":[120],"traditional":[122],"without":[124],"feature":[125],"enhancement":[126],"good":[129],"innovative":[130],"practical":[132],"value.":[133]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}