Hyperspectral Image Recovery Using Nonconvex Sparsity and Low-Rank Regularizations.
Yue HuXiaodi LiYanfeng GuMathews JacobPublished in: IEEE Trans. Geosci. Remote. Sens. (2020)
Keyphrases
- low rank
- group lasso
- hyperspectral images
- convex optimization
- low rank matrices
- robust principal component analysis
- hyperspectral
- minimization problems
- low rank matrix
- linear combination
- missing data
- remote sensing
- low rank and sparse
- matrix factorization
- matrix completion
- multispectral
- singular value decomposition
- semi supervised
- rank minimization
- high order
- target detection
- high dimensional data
- regularized regression
- total variation
- infrared
- small number
- image processing
- image data
- high dimensional
- multiscale
- feature selection
- multispectral images
- convex relaxation
- sparse representation