Nonlocal Linear Image Regularization and Supervised Segmentation

The steepest descent for minimizing the functional is interpreted as a nonlocal diffusion process, which allows a convenient framework for nonlocal variational minimizations, including variational denoising, Bregman iterations, and the recently proposed inverse scale space.