Hyperspectral Target Detection Based on Low-Rank Background Subspace Learning and Graph Laplacian Regularization.
Dunbin ShenXiaorui MaWenfeng KongJiacheng TianHongyu WangPublished in: CoRR (2023)
Keyphrases
- low rank
- graph laplacian
- subspace learning
- target detection
- hyperspectral
- high dimensional data
- semi supervised
- dimensionality reduction
- euclidean space
- spectral clustering
- low dimensional
- remote sensing
- infrared
- missing data
- multispectral
- linear combination
- singular value decomposition
- convex optimization
- manifold learning
- matrix factorization
- image data
- sparse coding
- principal component analysis
- kernel matrix
- high dimensional
- pairwise
- sparse representation
- face recognition
- learning algorithm
- nearest neighbor
- data points
- unsupervised learning
- higher order
- supervised learning
- dimension reduction
- feature extraction
- data analysis
- pattern recognition
- support vector
- machine learning
- clustering method
- kernel learning
- computer vision
- image processing
- similarity measure
- image analysis
- active learning
- state space
- high dimensionality
- small number