Dimensionality Reduction for Hyperspectral Image Based on Manifold Learning.
Yiting WangShiqi HuangHongxia WangDaizhi LiuZhigang LiuPublished in: ICIG (2) (2015)
Keyphrases
- manifold learning
- hyperspectral
- dimensionality reduction
- remote sensing
- low dimensional
- nonlinear dimensionality reduction
- hyperspectral images
- high dimensional data
- infrared
- multispectral
- high dimensional
- subspace learning
- diffusion maps
- image data
- principal component analysis
- dimensionality reduction methods
- pattern recognition
- feature extraction
- random projections
- high dimensionality
- feature selection
- feature space
- multi band
- locally linear embedding
- satellite images
- singular value decomposition
- principal components
- sparse representation
- input space
- information content
- dimension reduction
- linear discriminant analysis
- lower dimensional
- unsupervised learning
- manifold structure
- neural network
- nonlinear manifold
- semi supervised
- computer vision
- riemannian manifolds
- principal components analysis
- euclidean space
- data points
- image analysis