Implementation of the Principal Component Analysis onto High-Performance Computer Facilities for Hyperspectral Dimensionality Reduction: Results and Comparisons.
Ernestina MartelRaquel LazcanoJosé Francisco LópezDaniel MadroñalRubén SalvadorSebastián LópezEduardo Juárez MartínezRaúl GuerraCésar SanzRoberto SarmientoPublished in: Remote. Sens. (2018)
Keyphrases
- hyperspectral
- dimensionality reduction
- principal component analysis
- principal components
- remote sensing
- multispectral
- hyperspectral data
- hyperspectral imagery
- hyperspectral images
- dimension reduction
- low dimensional
- random projections
- linear discriminant analysis
- infrared
- spectral imagery
- high dimensional data
- high dimensional
- hyperspectral imaging
- target detection
- image data
- hyperspectral remote sensing
- hyperspectral image classification
- satellite images
- parallel computers
- lower dimensional
- independent component analysis
- feature extraction
- information content
- spatial resolution
- covariance matrix
- dimensionality reduction methods
- multi band
- pixel classification
- spectral data
- feature space
- feature selection
- face recognition
- spectral bands
- data points
- singular value decomposition
- pattern recognition
- high dimensionality
- data sets
- image reconstruction
- discriminant analysis