A nonconvex nonsmooth regularization method for compressed sensing and low rank matrix completion.
Zhuo-Xu CuiQibin FanPublished in: Digit. Signal Process. (2017)
Keyphrases
- compressed sensing
- matrix completion
- low rank
- convex optimization
- low rank matrices
- image reconstruction
- regularization parameter
- missing data
- low rank matrix
- linear combination
- image restoration
- sparse representation
- random projections
- kernel matrix
- total variation
- high dimensional data
- natural images
- matrix factorization
- singular value decomposition
- signal processing
- high order
- semi supervised
- objective function
- optimization problems
- image denoising
- convex relaxation
- computer vision
- image processing
- motion estimation
- optical flow
- denoising
- feature extraction
- collaborative filtering