Transfomer Based Hyperspectral Dimensionality Reduction with Gabor Kernel CNN for Feature Extraction.
Harshula TulapurkarB. Krishna MohanBiplab BanerjeePublished in: IGARSS (2023)
Keyphrases
- hyperspectral
- feature extraction
- dimensionality reduction
- feature space
- kernel pca
- remote sensing
- hyperspectral data
- kernel trick
- hyperspectral images
- multispectral
- input space
- feature vectors
- infrared
- random projections
- principal component analysis
- hyperspectral imagery
- image data
- pixel classification
- kernel function
- face recognition
- target detection
- hyperspectral imaging
- gabor filters
- kernel learning
- linear discriminant analysis
- high dimensionality
- gabor wavelets
- low dimensional
- dimensionality reduction methods
- pattern recognition
- hyperspectral remote sensing
- image processing
- principal components
- manifold learning
- hyperspectral image classification
- high dimensional feature space
- image classification
- dimension reduction
- principle component analysis
- high dimensional data
- spatial resolution
- feature selection
- frequency domain
- lower dimensional
- satellite images
- information content
- support vector
- spectral bands
- discriminant analysis
- kernel methods
- image representation
- change detection
- kernel based nonlinear
- feature set
- high dimensional
- support vector machine
- image analysis
- high resolution
- reflectance spectra
- singular value decomposition
- sparse representation
- texture features