Tensor Based Multiscale Low Rank Decomposition for Hyperspectral Images Dimensionality Reduction.
Jinliang AnJinhui LeiYuzhen SongXiangrong ZhangJinmei GuoPublished in: Remote. Sens. (2019)
Keyphrases
- low rank
- hyperspectral images
- dimensionality reduction
- multiscale
- high dimensional data
- singular value decomposition
- high order
- subspace learning
- tensor decomposition
- hyperspectral
- remote sensing
- principal component analysis
- kernel matrix
- missing data
- data representation
- convex optimization
- matrix factorization
- linear combination
- high dimensional
- low dimensional
- high dimensionality
- kernel learning
- multispectral
- manifold learning
- dimension reduction
- principal components
- sparse representation
- semi supervised
- image processing
- image segmentation
- feature extraction
- image fusion
- higher order
- wavelet transform
- data sets
- original data
- data points
- feature selection
- pattern recognition
- image representation
- neural network
- target detection
- data analysis
- random projections
- feature space
- pairwise
- natural images