Iteratively Regularized Gauss-Newton Method for Nonlinear Inverse Problems with Random Noise.
Frank BauerThorsten HohageAxel MunkPublished in: SIAM J. Numer. Anal. (2009)
Keyphrases
- random noise
- inverse problems
- newton method
- regularized least squares
- image reconstruction
- global optimization
- convex optimization
- convergence analysis
- variational inequalities
- linear equations
- optimization methods
- optimization problems
- sparse representation
- least squares
- partial differential equations
- early vision
- global convergence
- optimality conditions
- convex sets
- linear svm
- parameter space
- multiscale
- image enhancement
- reproducing kernel hilbert space
- text categorization
- particle swarm optimization
- super resolution