Spectral-Locational-Spatial Manifold Learning for Hyperspectral Images Dimensionality Reduction.
Na LiDeyun ZhouJiao ShiTao WuMaoguo GongPublished in: Remote. Sens. (2021)
Keyphrases
- manifold learning
- hyperspectral images
- dimensionality reduction
- spectral signatures
- hyperspectral
- hyperspectral imagery
- hyperspectral data
- low dimensional
- nonlinear dimensionality reduction
- random projections
- high dimensional data
- high dimensional
- diffusion maps
- spectral bands
- remote sensing
- principal component analysis
- high dimensionality
- feature extraction
- pattern recognition
- multispectral images
- dimensionality reduction methods
- locally linear embedding
- linear discriminant analysis
- multispectral
- spatial information
- feature space
- principal components
- data points
- dimension reduction
- unsupervised learning
- input space
- feature selection
- semi supervised
- lower dimensional
- manifold structure
- singular value decomposition
- machine learning
- face recognition
- kernel trick
- target detection
- geodesic distance
- training set
- image analysis
- video sequences
- image data
- data sets