{"id":"https://openalex.org/W4404628378","doi":"https://doi.org/10.1109/ipta62886.2024.10755689","title":"Hyperspectral Image Dimensionality Reduction Using Inter-Band Cross-Correlation and K-Means Clustering Algorithm","display_name":"Hyperspectral Image Dimensionality Reduction Using Inter-Band Cross-Correlation and K-Means Clustering Algorithm","publication_year":2024,"publication_date":"2024-10-14","ids":{"openalex":"https://openalex.org/W4404628378","doi":"https://doi.org/10.1109/ipta62886.2024.10755689"},"language":"en","primary_location":{"id":"doi:10.1109/ipta62886.2024.10755689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta62886.2024.10755689","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Thirteenth International Conference on Image Processing Theory, Tools and Applications (IPTA)","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/A5064310706","display_name":"Henry Ndu","orcid":"https://orcid.org/0009-0000-1417-232X"},"institutions":[{"id":"https://openalex.org/I84027002","display_name":"Leeds Beckett University","ror":"https://ror.org/02xsh5r57","country_code":"GB","type":"education","lineage":["https://openalex.org/I84027002"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Henry Ndu","raw_affiliation_strings":["School of Built Environment, Engineering and Computing, Leeds Beckett University,Leeds,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Built Environment, Engineering and Computing, Leeds Beckett University,Leeds,United Kingdom","institution_ids":["https://openalex.org/I84027002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041587191","display_name":"Akbar Sheikh-Akbari","orcid":"https://orcid.org/0000-0003-0677-7083"},"institutions":[{"id":"https://openalex.org/I84027002","display_name":"Leeds Beckett University","ror":"https://ror.org/02xsh5r57","country_code":"GB","type":"education","lineage":["https://openalex.org/I84027002"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Akbar Sheikh-Akbari","raw_affiliation_strings":["School of Built Environment, Engineering and Computing, Leeds Beckett University,Leeds,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Built Environment, Engineering and Computing, Leeds Beckett University,Leeds,United Kingdom","institution_ids":["https://openalex.org/I84027002"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014940645","display_name":"Koushlendra Kumar Singh","orcid":"https://orcid.org/0000-0002-5614-6098"},"institutions":[{"id":"https://openalex.org/I187761245","display_name":"National Institute of Technology Jamshedpur","ror":"https://ror.org/01sebzx27","country_code":"IN","type":"education","lineage":["https://openalex.org/I187761245"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Koushlendra K. Singh","raw_affiliation_strings":["Machine Vision and Intelligence Lab, National Institute of Technology,Jamshedpur,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Vision and Intelligence Lab, National Institute of Technology,Jamshedpur,India","institution_ids":["https://openalex.org/I187761245"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6631,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68585748,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"06"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.8931000232696533,"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"}},"topics":[{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.8931000232696533,"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":0.8553000092506409,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.8532000184059143,"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":0.7828123569488525},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.764427900314331},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7441771030426025},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6086969375610352},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5570844411849976},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.547881543636322},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.518462598323822},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.43864336609840393},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4338374137878418},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3991614580154419},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22116994857788086}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7828123569488525},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.764427900314331},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7441771030426025},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6086969375610352},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5570844411849976},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.547881543636322},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.518462598323822},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.43864336609840393},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4338374137878418},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3991614580154419},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22116994857788086},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ipta62886.2024.10755689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta62886.2024.10755689","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Thirteenth International Conference on Image Processing Theory, Tools and Applications (IPTA)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.leedsbeckett.ac.uk:11245","is_oa":false,"landing_page_url":"https://eprints.leedsbeckett.ac.uk/view/creators/Ndu=3AH=3A=3A.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4306400805","display_name":"Leeds Beckett Repository (Leeds Beckett University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I84027002","host_organization_name":"Leeds Beckett University","host_organization_lineage":["https://openalex.org/I84027002"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"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/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W2070598848","https://openalex.org/W2019190440","https://openalex.org/W2292979300"],"abstract_inverted_index":{"Hyperspectral":[0],"imaging":[1],"has":[2],"become":[3],"crucial":[4],"in":[5,16,148,187],"various":[6],"domains,":[7],"especially":[8],"for":[9,50,145,165],"the":[10,21,59,73,87,108,112,136,166,180],"accurate":[11],"detection":[12,147],"of":[13,72,105],"human":[14],"veins":[15],"medical":[17],"diagnostics,":[18],"though":[19],"managing":[20],"extensive":[22],"data":[23,33],"from":[24],"hyperspectral":[25],"(HS)":[26],"images":[27,52],"remains":[28],"a":[29,46,79,103],"challenge.":[30],"To":[31],"improve":[32],"handling":[34],"during":[35],"analysis,":[36],"dimensionality":[37,47,131],"reduction":[38,48,132],"methods":[39],"are":[40],"frequently":[41],"utilized.":[42],"This":[43],"paper":[44],"presents":[45],"method":[49,65,133,168,182],"HS":[51,54,75,119,149],"using":[53],"image":[55,120,127,153],"inter-band":[56,67],"cross-correlation":[57],"and":[58,93,169,174,185],"K-means":[60],"clustering":[61,97],"algorithm.":[62],"The":[63,95,117,129,151],"proposed":[64,130,167,181],"computes":[66],"correlations":[68],"across":[69],"all":[70],"bands":[71],"input":[74],"image,":[76],"which":[77],"form":[78],"2D":[80],"correlation":[81],"matrix.":[82],"Eigen-decomposition":[83],"is":[84,99,121],"applied":[85,101],"to":[86,102,157],"resulting":[88],"matrix,":[89],"extracting":[90],"its":[91],"eigenvectors":[92,106,113],"eigenvalues.":[94],"k-mean":[96],"algorithm":[98],"then":[100,143],"selection":[104],"representing":[107],"largest":[109],"eigenvalues,":[110],"splitting":[111],"into":[114],"several":[115],"clusters.":[116],"reduced":[118],"generated":[122,164],"by":[123],"averaging":[124],"each":[125],"cluster's":[126],"bands.":[128],"together":[134],"with":[135],"Support":[137],"Vector":[138],"Machine":[139],"(SVM)":[140],"classifier":[141],"was":[142,155],"used":[144,156],"vein":[146],"images.":[150],"HyperVein":[152],"dataset":[154],"generate":[158],"experimental":[159],"results.":[160],"Experimental":[161],"results":[162],"were":[163],"Principal":[170],"Component":[171],"Analysis":[172],"(PCA)":[173],"Folded":[175],"PCA":[176,184],"(FPCA).":[177],"Results":[178],"show":[179],"outperforms":[183],"FPCA":[186],"most":[188],"performance":[189],"metrics.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}