{"id":"https://openalex.org/W2919687913","doi":"https://doi.org/10.1145/3290420.3290475","title":"Clustering based spatial spectral preprocessing for hyperspectral unmxing","display_name":"Clustering based spatial spectral preprocessing for hyperspectral unmxing","publication_year":2018,"publication_date":"2018-11-02","ids":{"openalex":"https://openalex.org/W2919687913","doi":"https://doi.org/10.1145/3290420.3290475","mag":"2919687913"},"language":"en","primary_location":{"id":"doi:10.1145/3290420.3290475","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3290420.3290475","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Conference on Communication and Information Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5060761737","display_name":"Xiangfei Shen","orcid":"https://orcid.org/0000-0002-5501-4528"},"institutions":[{"id":"https://openalex.org/I3019309368","display_name":"North Minzu University","ror":"https://ror.org/05xjevr11","country_code":"CN","type":"education","lineage":["https://openalex.org/I3019309368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangfei Shen","raw_affiliation_strings":["North Minzu University, YinChuan, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Minzu University, YinChuan, P.R.China","institution_ids":["https://openalex.org/I3019309368"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046538842","display_name":"Wenxing Bao","orcid":"https://orcid.org/0000-0002-0267-5824"},"institutions":[{"id":"https://openalex.org/I3019309368","display_name":"North Minzu University","ror":"https://ror.org/05xjevr11","country_code":"CN","type":"education","lineage":["https://openalex.org/I3019309368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wexing Bao","raw_affiliation_strings":["North Minzu University, YinChuan, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Minzu University, YinChuan, P.R.China","institution_ids":["https://openalex.org/I3019309368"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076778682","display_name":"Kewen Qu","orcid":"https://orcid.org/0000-0001-5532-4107"},"institutions":[{"id":"https://openalex.org/I3019309368","display_name":"North Minzu University","ror":"https://ror.org/05xjevr11","country_code":"CN","type":"education","lineage":["https://openalex.org/I3019309368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kewen Qu","raw_affiliation_strings":["North Minzu University, YinChuan, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Minzu University, YinChuan, P.R.China","institution_ids":["https://openalex.org/I3019309368"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3019309368"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"313","last_page":"316"},"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":0.9926000237464905,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.955371618270874},{"id":"https://openalex.org/keywords/endmember","display_name":"Endmember","score":0.9364094138145447},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.7843969464302063},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6776490211486816},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6620506644248962},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6361606121063232},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6080725789070129},{"id":"https://openalex.org/keywords/spatial-contextual-awareness","display_name":"Spatial contextual awareness","score":0.5785307288169861},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5679993033409119},{"id":"https://openalex.org/keywords/homogeneity","display_name":"Homogeneity (statistics)","score":0.559891939163208},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5562148094177246},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4678303301334381},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.4344877600669861},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4290462136268616},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.413695752620697},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3759552538394928},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31798774003982544},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.14757642149925232},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0938149094581604},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.06793946027755737}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.955371618270874},{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.9364094138145447},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7843969464302063},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6776490211486816},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6620506644248962},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6361606121063232},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6080725789070129},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.5785307288169861},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5679993033409119},{"id":"https://openalex.org/C142259097","wikidata":"https://www.wikidata.org/wiki/Q5891314","display_name":"Homogeneity (statistics)","level":2,"score":0.559891939163208},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5562148094177246},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4678303301334381},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.4344877600669861},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4290462136268616},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.413695752620697},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3759552538394928},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31798774003982544},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.14757642149925232},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0938149094581604},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.06793946027755737},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3290420.3290475","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3290420.3290475","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Conference on Communication and Information Processing","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":20,"referenced_works":["https://openalex.org/W1582058549","https://openalex.org/W1588948804","https://openalex.org/W1964946444","https://openalex.org/W1976615758","https://openalex.org/W2023307693","https://openalex.org/W2059976262","https://openalex.org/W2070781258","https://openalex.org/W2087263574","https://openalex.org/W2095343758","https://openalex.org/W2102159812","https://openalex.org/W2114486983","https://openalex.org/W2128090514","https://openalex.org/W2130939260","https://openalex.org/W2156220628","https://openalex.org/W2157321686","https://openalex.org/W2163886442","https://openalex.org/W2295820431","https://openalex.org/W2336230670","https://openalex.org/W2766528611","https://openalex.org/W4233760599"],"related_works":["https://openalex.org/W3148227991","https://openalex.org/W1486593826","https://openalex.org/W2039721451","https://openalex.org/W2086636525","https://openalex.org/W2078337712","https://openalex.org/W3036216071","https://openalex.org/W2771174107","https://openalex.org/W1536965844","https://openalex.org/W2120787608","https://openalex.org/W2344941099"],"abstract_inverted_index":{"Numerous":[0],"spectral-based":[1],"endmember":[2,120],"extraction":[3],"algorithms":[4],"(EEAs)":[5],"for":[6,136],"hyperspectral":[7,53,129],"unmixing":[8],"(HU)":[9],"at":[10],"the":[11,58,65,71,74,90,101,107,117,141],"price":[12],"of":[13,36,100,109,119],"ignoring":[14],"spatial":[15,81,143],"context":[16],"information":[17,84],"in":[18,70],"recent":[19],"years.":[20],"In":[21],"this":[22],"paper,":[23],"we":[24],"propose":[25],"a":[26,133],"novel":[27],"preprocessing":[28,144],"module":[29],"by":[30,126],"integrating":[31],"spatial-spectral":[32],"information,":[33],"which":[34],"consists":[35],"three":[37],"parts:":[38],"1)":[39],"k-means":[40],"algorithm":[41,103],"based":[42],"on":[43],"spectral":[44,83],"angle":[45],"distance":[46],"measurement":[47],"criterion":[48],"is":[49,61,86,104],"used":[50],"to":[51,63,88,93,105],"identify":[52],"image":[54,95,110],"homogenous":[55],"regions;":[56],"2)":[57],"local":[59],"window":[60],"utilized":[62],"detect":[64],"anomalous":[66,91],"pixels":[67,92],"that":[68,77],"hide":[69],"scene;":[72],"3)":[73],"reconstruction":[75],"weight":[76],"takes":[78],"into":[79],"account":[80],"and":[82,111],"jointly":[85],"designed":[87],"revise":[89],"strengthen":[94],"homogeneity.":[96],"The":[97,122],"principal":[98],"contribution":[99],"proposed":[102],"promote":[106],"homogeneity":[108],"lessen":[112],"computational":[113],"complexity":[114],"while":[115,138],"improving":[116],"accuracy":[118],"extraction.":[121],"experimental":[123],"results":[124],"obtained":[125],"using":[127],"real":[128],"data":[130],"set":[131],"show":[132],"slight":[134],"improvement":[135],"HU":[137],"comparing":[139],"with":[140],"state-of-art":[142],"framework.":[145]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
