On the performance of random-projection-based dimensionality reduction for endmember extraction.
Qian DuJames E. FowlerPublished in: IGARSS (2010)
Keyphrases
- dimensionality reduction
- high dimensional data
- high dimensional
- hyperspectral imagery
- high dimensionality
- pattern recognition
- automatic extraction
- data representation
- low dimensional
- information extraction
- hyperspectral images
- dimensionality reduction methods
- principal component analysis
- structure preserving
- singular value decomposition
- pattern recognition and machine learning
- linear discriminant analysis
- computationally efficient
- data points
- dimension reduction
- manifold learning
- input space
- knowledge extraction
- feature selection
- search engine
- neural network
- principal components
- feature extraction
- uniformly distributed
- kernel pca
- nonlinear dimensionality reduction
- genetic algorithm
- machine learning