Dimension Reduction Using Spatial and Spectral Regularized Local Discriminant Embedding for Hyperspectral Image Classification.
Yicong ZhouJiangtao PengC. L. Philip ChenPublished in: IEEE Trans. Geosci. Remote. Sens. (2015)
Keyphrases
- dimension reduction
- hyperspectral image classification
- discriminant embedding
- hyperspectral
- hyperspectral images
- manifold learning
- active learning
- hyperspectral data
- principal component analysis
- random projections
- feature extraction
- low dimensional
- high dimensional data
- high dimensional
- linear discriminant analysis
- high dimensionality
- singular value decomposition
- multispectral
- discriminative information
- remote sensing
- dimensionality reduction
- face recognition
- graph embedding
- hyperspectral imagery
- feature space
- preprocessing
- small sample size
- feature selection
- infrared
- principle component analysis
- support vector
- cluster analysis
- semi supervised
- image data
- least squares
- pattern recognition