On the limitation of convex optimization for sparse signal segmentation.
Pavel RajmicMichaela NovosadovaPublished in: TSP (2016)
Keyphrases
- convex optimization
- basis pursuit
- norm regularization
- interior point methods
- compressive sensing
- low rank
- signal recovery
- primal dual
- image segmentation
- convex relaxation
- total variation
- signal processing
- low rank matrix
- low rank textures
- convex optimization problems
- level set
- group lasso
- norm minimization
- image processing
- low rank and sparse
- compressed sensing
- denoising
- multiscale
- computer vision
- semidefinite programming
- sparse representation