Patch-Ordering for Regularizing Inverse Problems

In an earlier work we have shown that extracting all the overlapping patches from an image and ordering them to form the shortest path could be used in various ways to gain non-local processing of visual data. In our 2016 paper published in SIAM Journal on Imaging Sciences, Grisha Vaksman and I show how this could be used to regularized general inverse problems in imaging. We demonstrate the proposed scheme on a diverse set of problems: (i) severe Poisson image denoising, (ii) Gaussian image denoising, (iii) image deblurring, and (iv) single image super-resolution.This package contains all the necessary code to reproduce the experiments in this paper.