Spatial-Spectral Graph-Based Nonlinear Embedding Dimensionality Reduction for Hyperspectral Image Classificaiton.
Xiangrong ZhangYaru HanNing HuyanChen LiJie FengLi GaoXiaoxiao MaPublished in: IGARSS (2018)
Keyphrases
- hyperspectral images
- spectral signatures
- dimensionality reduction
- hyperspectral imagery
- hyperspectral
- nonlinear dimensionality reduction
- hyperspectral data
- semi supervised dimensionality reduction
- graph embedding
- frequency domain
- kernel pca
- random projections
- high dimensional feature space
- kernel based nonlinear
- linear dimensionality reduction
- high dimensional data
- low dimensional
- spatial frequency
- spectral bands
- high dimensional
- remote sensing
- high dimensionality
- hyperspectral imaging
- hyperspectral image classification
- spatial information
- feature extraction
- band selection
- embedding space
- spectral data
- feature selection
- target detection
- multispectral
- infrared
- pattern recognition
- satellite images
- manifold learning
- information content
- principal component analysis
- spectral resolution
- feature space
- principal components
- pixel classification
- denoising
- image data
- reflectance spectra
- hyperspectral remote sensing
- spatial domain