SLIC Superpixel-Based l(2,1)-Norm Robust Principal Component Analysis for Hyperspectral Image Classification

Hyperspectral Images (HSIs) contain enriched information due to the presence of various bands, which have gained attention for the past few decades. However, explosive growth in HSIs’ scale and dimensions causes “Curse of dimensionality” and “Hughes phenomenon”. Dimensionality reduction has become a...

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Detalles Bibliográficos
Autores principales: Zu, Baokai, Xia, Kewen, Li, Tiejun, He, Ziping, Li, Yafang, Hou, Jingzhong, Du, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386951/
https://www.ncbi.nlm.nih.gov/pubmed/30682823
http://dx.doi.org/10.3390/s19030479

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386951/
https://www.ncbi.nlm.nih.gov/pubmed/30682823
http://dx.doi.org/10.3390/s19030479

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