{"id":"https://openalex.org/W2074932183","doi":"https://doi.org/10.1109/lgrs.2015.2389269","title":"Nonlinear PCA for Visible and Thermal Hyperspectral Images Quality Enhancement","display_name":"Nonlinear PCA for Visible and Thermal Hyperspectral Images Quality Enhancement","publication_year":2015,"publication_date":"2015-03-02","ids":{"openalex":"https://openalex.org/W2074932183","doi":"https://doi.org/10.1109/lgrs.2015.2389269","mag":"2074932183"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2015.2389269","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2015.2389269","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5078994593","display_name":"Giorgio Licciardi","orcid":"https://orcid.org/0000-0003-4259-919X"},"institutions":[{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4210124956","display_name":"GIPSA-Lab","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"G. A. Licciardi","raw_affiliation_strings":["GIPSA-Lab, Grenoble Institute of Technology, Grenoble, France","[GIPSA-lab, Grenoble Institute of Technology, Grenoble, France]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"GIPSA-Lab, Grenoble Institute of Technology, Grenoble, France","institution_ids":["https://openalex.org/I106785703","https://openalex.org/I4210124956"]},{"raw_affiliation_string":"[GIPSA-lab, Grenoble Institute of Technology, Grenoble, France]","institution_ids":["https://openalex.org/I106785703","https://openalex.org/I4210124956"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106124934","display_name":"Jocelyn Chanussot","orcid":"https://orcid.org/0000-0003-4817-2875"},"institutions":[{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]},{"id":"https://openalex.org/I4210124956","display_name":"GIPSA-Lab","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]}],"countries":["FR","IS"],"is_corresponding":false,"raw_author_name":"J. Chanussot","raw_affiliation_strings":["GIPSA-Lab, University of Iceland, Reykjav\u00edk, Iceland","[GIPSA-lab, Grenoble Institute of Technology, Grenoble, France]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"GIPSA-Lab, University of Iceland, Reykjav\u00edk, Iceland","institution_ids":["https://openalex.org/I165368041"]},{"raw_affiliation_string":"[GIPSA-lab, Grenoble Institute of Technology, Grenoble, France]","institution_ids":["https://openalex.org/I106785703","https://openalex.org/I4210124956"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.3049,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.93182668,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"12","issue":"6","first_page":"1228","last_page":"1231"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9988999962806702,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9986000061035156,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9519037008285522},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7378593683242798},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6419047713279724},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6367506980895996},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5606884360313416},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.530390202999115},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5188432931900024},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4755953252315521},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47269630432128906},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45919573307037354},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.4177474081516266},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4148826599121094},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35366272926330566},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.31746965646743774},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06638801097869873}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9519037008285522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7378593683242798},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6419047713279724},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6367506980895996},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5606884360313416},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.530390202999115},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5188432931900024},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4755953252315521},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47269630432128906},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45919573307037354},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.4177474081516266},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4148826599121094},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35366272926330566},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31746965646743774},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06638801097869873},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2015.2389269","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2015.2389269","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1554663460","https://openalex.org/W1679913846","https://openalex.org/W1768150715","https://openalex.org/W1994040806","https://openalex.org/W2004104348","https://openalex.org/W2053186076","https://openalex.org/W2078404340","https://openalex.org/W2105732805","https://openalex.org/W2121561691","https://openalex.org/W2122538988","https://openalex.org/W2131329059","https://openalex.org/W2133396101","https://openalex.org/W2140095548","https://openalex.org/W2141494774","https://openalex.org/W2155124307","https://openalex.org/W2161073299","https://openalex.org/W4245176872","https://openalex.org/W4388297464","https://openalex.org/W6676014314"],"related_works":["https://openalex.org/W2911259277","https://openalex.org/W4386427838","https://openalex.org/W2800956885","https://openalex.org/W2533019003","https://openalex.org/W2057283258","https://openalex.org/W2626158795","https://openalex.org/W1788560349","https://openalex.org/W2391021239","https://openalex.org/W2095129185","https://openalex.org/W2166564037"],"abstract_inverted_index":{"In":[0],"this":[1],"letter,":[2],"we":[3],"propose":[4],"a":[5,58,72],"method":[6],"aiming":[7],"at":[8,49],"reducing":[9],"the":[10,17,36,46,50,61,65,98,101,119,122],"noise":[11,79],"in":[12,71,95],"hyperspectral":[13,37,66,103,110],"images":[14,111],"based":[15],"on":[16,108],"nonlinear":[18,62,84],"generalization":[19],"of":[20,97,100,121],"principal":[21],"component":[22],"analysis":[23],"(NLPCA).":[24],"NLPCA":[25],"is":[26,42],"performed":[27],"by":[28,57,77],"an":[29],"autoassociative":[30],"neural":[31],"network":[32],"(AANN)":[33],"that":[34],"has":[35],"image":[38,48,67],"as":[39,125,131],"input":[40],"and":[41,80,83,114,117,133],"trained":[43],"to":[44,53,68,92],"reconstruct":[45],"same":[47],"output.":[51],"Due":[52],"its":[54],"topology,":[55],"characterized":[56],"bottleneck":[59],"layer,":[60],"AANN":[63],"forces":[64],"be":[69],"projected":[70],"lower":[73],"dimensionality":[74],"feature":[75],"space":[76],"removing":[78],"both":[81],"linear":[82],"correlations":[85],"between":[86],"spectral":[87],"bands.":[88],"This":[89],"process":[90],"permits":[91],"obtain":[93],"enhancements":[94],"terms":[96],"quality":[99],"reconstructed":[102],"image.":[104],"The":[105],"results":[106],"conducted":[107],"different":[109],"are":[112],"qualitatively":[113],"quantitatively":[115],"discussed":[116],"demonstrate":[118],"potentialities":[120],"proposed":[123],"method,":[124],"compared":[126],"with":[127],"similar":[128],"approaches":[129],"such":[130],"PCA":[132],"kernel":[134],"PCA.":[135]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
