Joint-Sparse-Blocks Regression for Total Variation Regularized Hyperspectral Unmixing.
Jie HuangTing-Zhu HuangXi-Le ZhaoLiang-Jian DengPublished in: IEEE Access (2019)
Keyphrases
- hyperspectral
- total variation
- regularization methods
- image restoration
- hyperspectral images
- denoising
- hyperspectral data
- image denoising
- remote sensing
- sparse regression
- regularized least squares
- multispectral
- infrared
- regularization term
- convex optimization
- regression model
- hyperspectral imagery
- image processing
- total least squares
- image data
- regularization method
- information content
- spatial resolution
- canonical correlation analysis
- target detection
- satellite images
- random projections
- sparsity inducing
- high dimensional
- reproducing kernel hilbert space
- least squares
- noisy images
- low dimensional
- group lasso
- sparse representation
- frequency domain
- super resolution
- multiresolution
- pairwise
- object recognition
- high quality
- image sequences