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Bilevel Learning Approaches in Variational Image
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- 1 Intro
- 2 Outline
- 3 A generic inverse problem in imaging
- 4 The variational approach..
- 5 Modelling
- 6 Total variation (TV) denoising Least squares minimization
- 7 Modified non-local means Giboa Osher (2007)
- 8 State of the art in optimal model design
- 9 Bilevel optimal reconstruction model Assumptions
- 10 Learning from training sets
- 11 Learning by optimisation in imaging
- 12 Learning in function space
- 13 A generic TV denoising model
- 14 Learning TV denoising model
- 15 State of the art on optimality systems
- 16 In this setting we can prove
- 17 Optimality system for the regularized problems
- 18 Optimality system for bilevel problem
- 19 Numerical notes
- 20 Mixed Gauss & Poisson noise
- 21 Impulse noise
- 22 Partial conclusions
- 23 Nonhomogeneous noise
- 24 Ingredients for optimality conditions
- 25 Experiments
- 26 Motivation
- 27 Forward denoising problem
- 28 The kernel
- 29 Different kernels, different results
- 30 Bilevel optimization problem Optimal weight
- 31 What we are trying to do..
- 32 Conclusions and outlook
