Tensor-Based Low-Rank Graph With Multimanifold Regularization for Dimensionality Reduction of Hyperspectral Images.
Jinliang AnXiangrong ZhangHuiyu ZhouLicheng JiaoPublished in: IEEE Trans. Geosci. Remote. Sens. (2018)
Keyphrases
- low rank
- hyperspectral images
- dimensionality reduction
- rank minimization
- high dimensional data
- trace norm
- singular value decomposition
- high order
- minimization problems
- subspace learning
- low rank and sparse
- hyperspectral
- matrix completion
- linear combination
- matrix factorization
- convex optimization
- remote sensing
- semi supervised
- missing data
- low rank matrix
- kernel matrix
- low dimensional
- high dimensional
- feature extraction
- multispectral
- principal component analysis
- manifold learning
- high dimensionality
- nearest neighbor
- pattern recognition
- multiscale
- higher order
- data points
- feature space
- original data
- image data
- data sets
- multispectral images
- target detection
- graph laplacian
- active learning
- dimension reduction