Higher order convergence rates for Bregman iterated variational regularization of inverse problems.
Benjamin SprungThorsten HohagePublished in: Numerische Mathematik (2019)
Keyphrases
- inverse problems
- convergence rate
- higher order
- image reconstruction
- convex optimization
- regularization methods
- global optimization
- regularization method
- total variation
- optimization methods
- learning rate
- natural images
- global convergence
- high order
- optimization problems
- pairwise
- primal dual
- denoising
- image segmentation
- partial differential equations
- markov random field
- optical flow
- gaussian kernels
- loss function
- smoothness constraint
- variational methods
- early vision
- computationally expensive
- super resolution
- regularization term
- state space
- image denoising
- high quality