On the Convergence of Primal-Dual Hybrid Gradient Algorithms for Total Variation Image Restoration.
Silvia BonettiniValeria RuggieroPublished in: J. Math. Imaging Vis. (2012)
Keyphrases
- image restoration
- total variation
- convex optimization
- primal dual
- minimization problems
- rudin osher fatemi
- dual formulation
- split bregman
- interior point
- convergence rate
- image deblurring
- augmented lagrangian
- denoising
- edge preserving
- image processing
- fidelity term
- regularization method
- augmented lagrangian method
- image denoising
- regularization term
- iterative image restoration
- interior point methods
- regularization methods
- super resolution
- half quadratic
- blurred images
- blind deconvolution
- regularization parameter
- linear programming
- image restoration problems
- total variation minimization
- computational complexity
- alternating minimization
- optimization problems
- markov random field
- computer vision
- color image restoration
- mumford shah
- motion blur
- total least squares
- inverse scale space
- restored image
- semidefinite programming
- gaussian noise
- image compression
- feature vectors
- multiscale