Local Kernels that Approximate Bayesian Regularization and Proximal Operators.

In this work, we broadly connect kernel-based filtering (e.g. approaches such as the bilateral filter and nonlocal means, but also many more) with general variational formulations of Bayesian regularized least squares, and the related concept of proximal operators.