Overview
Syllabus
Intro
Outline
A generic inverse problem in imaging
The variational approach..
Modelling
Total variation (TV) denoising Least squares minimization
Modified non-local means Giboa Osher (2007)
State of the art in optimal model design
Bilevel optimal reconstruction model Assumptions
Learning from training sets
Learning by optimisation in imaging
Learning in function space
A generic TV denoising model
Learning TV denoising model
State of the art on optimality systems
In this setting we can prove
Optimality system for the regularized problems
Optimality system for bilevel problem
Numerical notes
Mixed Gauss & Poisson noise
Impulse noise
Partial conclusions
Nonhomogeneous noise
Ingredients for optimality conditions
Experiments
Motivation
Forward denoising problem
The kernel
Different kernels, different results
Bilevel optimization problem Optimal weight
What we are trying to do..
Conclusions and outlook
Taught by
Hausdorff Center for Mathematics