mlsanityData to 14 Oct 2026

The jump set under geometric regularisation. Part 1: Basic technique and first-order denoising

arXiv 1407.1531 ↗First posted 6 Jul 2014math.FA cs.CVcited by 1

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Abstract (arXiv)

Let u ∈ mboxBV(Omega) solve the total variation denoising problem with L2-squared fidelity and data f. Caselles et al. [Multiscale Model. Simul. 6 (2008), 879--894] have shown the containment Hm-1(Ju setminus Jf)=0 of the jump set Ju of u in that of f. Their proof unfortunately depends heavily on the co-area formula, as do many results in this area, and as such is not directly extensible to higher-order, curvature-based, and other advanced geometric regularisers, such as total generalised variation (TGV) and Euler's elastica. These have received increased attention in recent times due to their better practical regularisation properties compared to conventional total variation or wavelets. We prove analogous jump set containment properties for a general class of regularisers. We do this with novel Lipschitz transformation techniques, and do not require the co-area formula. In the present Part 1 we demonstrate the general technique on first-order regularisers, while in Part 2 we will extend it to higher-order regularisers. In particular, we concentrate in this part on TV and, as a novelty, Huber-regularised TV. We also demonstrate that the technique would apply to non-convex TV models as well as the Perona-Malik anisotropic diffusion, if these approaches were well-posed to begin with.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 6 Jul 2014.

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