Dimensionality Reduction and Linear Discriminant Analysis for Hyperspectral Image Classification.
Qian DuNicolas H. YounanPublished in: KES (3) (2008)
Keyphrases
- linear discriminant analysis
- dimensionality reduction
- hyperspectral image classification
- discriminant analysis
- active learning
- hyperspectral
- hyperspectral images
- hyperspectral data
- random projections
- principal component analysis
- high dimensional data
- dimension reduction
- high dimensional
- feature extraction
- dimensionality reduction methods
- low dimensional
- data representation
- input space
- pattern recognition
- dealing with high dimensional data
- small sample size
- principal components analysis
- subspace methods
- data points
- linear discriminant
- lower dimensional
- feature space
- feature selection
- null space
- linear projection
- fisher criterion
- principal components
- high dimensionality
- face recognition
- metric learning
- remote sensing
- supervised dimensionality reduction
- knn
- infrared
- k nearest neighbor
- scatter matrix
- image data