= Huber gradient regularizer
{c}
A <Huber loss> applied to a discrete gradient combines quadratic penalization of small slopes with linear penalization of large slopes. This interpolates between squared-gradient smoothing and <total variation denoising>, allowing smooth regions while retaining an edge-preserving large-gradient regime. The threshold should be chosen consistently with the signal's units and discretization. It can reduce <staircasing in total variation denoising> without guaranteeing its elimination.
Back to article page
