Laplacian Eigenmaps-Based Polarimetric Dimensionality Reduction for SAR Image Classification.
Shang Tan TuJiayu ChenWen YangHong SunPublished in: IEEE Trans. Geosci. Remote. Sens. (2012)
Keyphrases
- laplacian eigenmaps
- dimensionality reduction
- image classification
- synthetic aperture radar
- sar imagery
- feature extraction
- manifold learning
- kernel pca
- nonlinear dimensionality reduction
- sar images
- locally linear embedding
- principal component analysis
- low dimensional
- dimensionality reduction methods
- high dimensional data
- high dimensional
- pattern recognition
- image reconstruction
- input space
- image representation
- sparse representation
- preprocessing step
- feature selection
- subspace learning
- lower dimensional
- image features
- data points
- high dimensionality
- principal components
- sparse coding
- kernel methods
- face recognition
- linear discriminant analysis
- singular value decomposition
- maximum likelihood
- discriminant analysis
- feature space
- random projections
- dimension reduction
- support vector machine
- principal components analysis
- euclidean distance
- multispectral
- kernel function
- metric learning
- feature vectors
- wavelet domain
- clustering method
- latent space
- multiscale
- spectral clustering