Limiting aspects of non-convex TVφ models
Abstract
Recently, non-convex regularisation models have been introduced in order to provide a better prior for gradient distributions in real images. They are based on using concave energies φ in the total variation type functional TVφ(u) := ∫ φ(|∇ u(x)|) d x. In this paper, it is demonstrated that for typical choices of φ, functionals of this type pose several difficulties when extended to the entire space of functions of bounded variation, BV(). In particular, if φ(t)=tq for q ∈ (0, 1) and TVφ is defined directly for piecewise constant functions and extended via weak* lower semicontinuous envelopes to BV(), then still TVφ(u)=∞ for u not piecewise constant. If, on the other hand, TVφ is defined analogously via continuously differentiable functions, then TVφ 0, (!). We study a way to remedy the models through additional multiscale regularisation and area strict convergence, provided that the energy φ(t)=tq is linearised for high values. The fact, that this kind of energies actually better matches reality and improves reconstructions, is demonstrated by statistics and numerical experiments.
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