Dimensionality Reduction of Hyperspectral Images With Sparse Discriminant Embedding.
Hong HuangMei YangPublished in: IEEE Trans. Geosci. Remote. Sens. (2015)
Keyphrases
- hyperspectral images
- dimensionality reduction
- discriminant embedding
- graph embedding
- high dimensional
- manifold learning
- discriminant information
- random projections
- sparse representation
- hyperspectral
- locality preserving
- low dimensional
- remote sensing
- face recognition
- feature extraction
- high dimensional data
- pattern classification
- principal component analysis
- data representation
- subspace learning
- small sample size
- multispectral
- linear discriminant analysis
- pattern recognition
- label information
- high dimensionality
- data points
- input space
- dictionary learning
- target detection
- feature selection
- feature space
- sparse coding
- embedding space
- dimensionality reduction methods
- locally linear embedding
- locality preserving projections
- lower dimensional
- principal components
- satellite images
- discriminant analysis
- high resolution
- image processing
- multispectral images
- kernel pca
- dimension reduction
- singular value decomposition
- low resolution
- high quality