Uncertainty Quantification in Imaging: When Convex Optimization Meets Bayesian Analysis.
Audrey RepettiMarcelo PereyraYves WiauxPublished in: EUSIPCO (2018)
Keyphrases
- convex optimization
- bayesian analysis
- computationally feasible
- convex optimization problems
- interior point methods
- image processing
- convex relaxation
- low rank
- high resolution
- total variation
- primal dual
- computer vision
- norm minimization
- convex formulation
- semidefinite program
- feature space
- operator splitting
- image compression
- linear programming
- higher order
- low rank matrix
- convex constraints