Nonlinear Unmixing of Hyperspectral Data With Vector-Valued Kernel Functions.
Rita AmmanouilAndré FerrariCédric RichardSandrine MathieuPublished in: IEEE Trans. Image Process. (2017)
Keyphrases
- hyperspectral data
- kernel function
- vector valued
- high dimensional feature space
- hyperspectral imagery
- reproducing kernel hilbert space
- hyperspectral
- hyperspectral images
- kernel methods
- kernel pca
- support vector
- random projections
- input space
- remote sensing
- multispectral
- feature space
- infrared
- scale space
- high dimensional
- support vector machine
- kernel matrix
- original data
- svm classifier
- principal components
- hyperplane
- support vectors
- diffusion equation
- image data
- wavelet packet
- low dimensional
- dimensionality reduction
- data compression
- learning problems
- feature selection
- pattern recognition
- classification accuracy
- zero crossing
- data dependent
- image features
- feature set