A comparative study of two globally convergent numerical methods for acoustic tomography.
Michael V. KlibanovAlexandre A. TimonovPublished in: CoRR (2023)
Keyphrases
- numerical methods
- globally convergent
- autocalibration
- variational inequalities
- image reconstruction
- differential equations
- newton method
- partial differential equations
- global convergence
- augmented lagrangian
- line search
- level set method
- limited angle
- constrained optimization
- sensitivity analysis
- feature selection
- convergence speed
- convex sets
- image enhancement
- natural images
- dynamic programming
- convergence analysis
- regularized least squares
- search space
- object recognition
- multiscale
- image sequences
- image processing