Local smoothness maps: a new method for solving inverse problems with the accurate recovery of sharp gradients

We describe a novel Bayesian approach to solving inverse problems by simultaneously estimating the reconstructed signal and the local smoothness map (LSM), which is a generalization of the global smoothness parameter that is often used to stabilize inverse problems. The greater flexibility afforded...

Ausführliche Beschreibung