Total variation flow
= Total variation flow
{title2=$u_t\in-\partial\operatorname{TV}(u)$}
Total variation flow is the $L^2$ <gradient flow> of the <total variation seminorm on a domain>. Formally it is $u_t=\operatorname{div}(\nabla u/|\nabla u|)$, but the <subgradient> formulation handles zero gradients and jumps. Adding quadratic fidelity gives a <strictly convex> stationary <total variation denoising> problem.