Dimensionality Reduction of Hyperspectral Images Based on Improved Spatial-Spectral Weight Manifold Embedding.
Hong LiuKewen XiaTiejun LiJie MaEunice OwoolaPublished in: Sensors (2020)
Keyphrases
- hyperspectral images
- dimensionality reduction
- manifold embedding
- hyperspectral
- hyperspectral imagery
- hyperspectral data
- manifold learning
- spectral bands
- remote sensing
- hyperspectral remote sensing
- low dimensional
- random projections
- head pose estimation
- multispectral
- dimension reduction
- spatial information
- multispectral images
- manifold structure
- target detection
- high dimensional data
- nonlinear dimensionality reduction
- subspace learning
- principal component analysis
- infrared
- principal components
- feature extraction
- high dimensional
- high dimensionality
- feature selection
- image data
- lower dimensional
- information content
- data points
- high resolution
- nearest neighbor
- moving objects
- feature space
- pattern recognition
- input space