Semisupervised Manifold Joint Hypergraphs for Dimensionality Reduction of Hyperspectral Image.
Yule DuanHong HuangYuxiao TangYuan LiChunyu PuPublished in: IEEE Geosci. Remote. Sens. Lett. (2021)
Keyphrases
- hyperspectral images
- dimensionality reduction
- manifold learning
- low dimensional
- semi supervised
- lower dimensional
- nonlinear dimensionality reduction
- hyperspectral
- high dimensional
- locally linear embedding
- remote sensing
- graph embedding
- hyperspectral imagery
- hyperspectral imaging
- high dimensional data
- hyperspectral data
- high dimensionality
- target detection
- pattern recognition
- feature space
- embedding space
- principal component analysis
- hyperspectral image classification
- multispectral
- feature extraction
- input space
- linear discriminant analysis
- dimension reduction
- dimensionality reduction methods
- euclidean space
- random projections
- principal components
- data points
- multispectral images
- reflectance spectra
- discriminant analysis
- image analysis
- feature selection
- satellite images
- color images
- active learning
- original data
- spatial resolution