{"id":"https://openalex.org/W2901388779","doi":"https://doi.org/10.1109/igarss.2018.8518082","title":"Hyperspectral Endmember Extraction Preprocessing Using Combination of Euclidean and Geodesic Distances","display_name":"Hyperspectral Endmember Extraction Preprocessing Using Combination of Euclidean and Geodesic Distances","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2901388779","doi":"https://doi.org/10.1109/igarss.2018.8518082","mag":"2901388779"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8518082","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518082","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/A5013686661","display_name":"Fatemeh Kowkabi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090965","display_name":"Islamic Azad University, Marvdasht","ror":"https://ror.org/00bqttt79","country_code":"IR","type":"education","lineage":["https://openalex.org/I4210090965"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Fatemeh Kowkabi","raw_affiliation_strings":["Department of Electrical Engineering, Islamic Azad University, Marvdasht, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Islamic Azad University, Marvdasht, Iran","institution_ids":["https://openalex.org/I4210090965"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026041687","display_name":"Ahmad Keshavarz","orcid":"https://orcid.org/0000-0002-5103-8311"},"institutions":[{"id":"https://openalex.org/I90767664","display_name":"Persian Gulf University","ror":"https://ror.org/03n2mgj60","country_code":"IR","type":"education","lineage":["https://openalex.org/I90767664"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Ahmad Keshavarz","raw_affiliation_strings":["Electrical Engineering Department, Persian Gulf University, Bushehr, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Persian Gulf University, Bushehr, Iran","institution_ids":["https://openalex.org/I90767664"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2092,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.60618815,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"4265","last_page":"4268"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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":0.9932000041007996,"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":0.9848999977111816,"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/endmember","display_name":"Endmember","score":0.9229023456573486},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9012353420257568},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7204026579856873},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6996457576751709},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6512136459350586},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5827368497848511},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5588020086288452},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5505502223968506},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5311424136161804},{"id":"https://openalex.org/keywords/geodesic","display_name":"Geodesic","score":0.45051708817481995},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38302743434906006},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3220319151878357},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.27326977252960205}],"concepts":[{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.9229023456573486},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9012353420257568},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7204026579856873},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6996457576751709},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6512136459350586},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5827368497848511},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5588020086288452},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5505502223968506},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5311424136161804},{"id":"https://openalex.org/C165818556","wikidata":"https://www.wikidata.org/wiki/Q213488","display_name":"Geodesic","level":2,"score":0.45051708817481995},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38302743434906006},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3220319151878357},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27326977252960205},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8518082","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518082","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1964946444","https://openalex.org/W2029786966","https://openalex.org/W2070424424","https://openalex.org/W2070781258","https://openalex.org/W2098295833","https://openalex.org/W2114486983","https://openalex.org/W2117741752","https://openalex.org/W2127062304","https://openalex.org/W2128090514","https://openalex.org/W2130939260","https://openalex.org/W2157321686","https://openalex.org/W2163886442","https://openalex.org/W2165755981","https://openalex.org/W2336230670","https://openalex.org/W2336417938","https://openalex.org/W2497342092","https://openalex.org/W2547872803","https://openalex.org/W2611619657","https://openalex.org/W3104040694","https://openalex.org/W4233760599","https://openalex.org/W6785645893"],"related_works":["https://openalex.org/W2037328426","https://openalex.org/W1990914742","https://openalex.org/W3106536224","https://openalex.org/W2891033441","https://openalex.org/W2006559622","https://openalex.org/W2890371384","https://openalex.org/W2773863718","https://openalex.org/W2315521504","https://openalex.org/W2563324120","https://openalex.org/W2040756827"],"abstract_inverted_index":{"Combination":[0],"the":[1,99,138,161,188],"spatial-contextual":[2],"information":[3],"in":[4,20,56,144,169],"spectral":[5,35,51,70,94,128],"unmixing":[6,184],"as":[7],"a":[8,28,83,116],"preprocessing":[9,30,110,152,179],"of":[10,34,53,102,105,115,119,150,163,183,194],"endmember":[11],"extraction":[12],"algorithms":[13],"(EEAs)":[14],"has":[15],"been":[16],"an":[17],"important":[18],"issue":[19],"hyperspectral":[21,158],"image":[22,54],"analysis.":[23],"Particularly,":[24],"this":[25,79],"paper":[26],"performs":[27],"new":[29,84,127],"framework":[31],"using":[32],"combination":[33],"Geodesic":[36,129],"and":[37,50,64,97,130,165,190],"spatial":[38,49,103,131],"Euclidean":[39,132],"distances":[40,133],"prior":[41],"to":[42,58,75,136],"classical":[43],"spectral-based":[44],"EEAs.":[45,124,196],"It":[46],"exploits":[47,143],"both":[48],"features":[52],"pixels":[55,91,121],"order":[57],"look":[59],"for":[60],"high":[61],"spectrally":[62],"correlated":[63],"spatially":[65,89],"homogenous":[66,90],"regions":[67],"where":[68],"pure":[69,106],"signatures":[71],"are":[72,134],"more":[73],"likely":[74],"be":[76],"found.":[77],"For":[78],"purpose,":[80],"it":[81],"exerts":[82],"correlation":[85,145],"coefficient":[86,146],"quantity":[87],"on":[88,155],"designated":[92],"by":[93,123],"weighting":[95],"determination":[96],"appraising":[98],"cluster":[100],"label":[101],"neighbours":[104],"pixels.":[107],"The":[108,148],"novel":[109],"hampers":[111],"from":[112,160],"useless":[113],"computation":[114],"great":[117],"number":[118],"mixed":[120],"executed":[122],"Additionally,":[125],"two":[126,156],"presented":[135],"specify":[137],"final":[139],"mean":[140],"vector":[141],"which":[142],"computations.":[147],"validation":[149],"our":[151],"is":[153],"deliberated":[154],"real":[157],"datasets":[159],"viewpoints":[162],"RMSE":[164],"SAD":[166],"based":[167],"errors":[168],"comparison":[170],"with":[171,191],"other":[172],"schemes.":[173],"Experimental":[174],"consequences":[175],"declare":[176],"that":[177],"such":[178],"can":[180],"amend":[181],"figures":[182],"accuracy":[185],"without":[186],"intensifying":[187],"complexity":[189],"no":[192],"requirement":[193],"changing":[195]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
