English

Cartoon Approximation with $\alpha$-Curvelets

Functional Analysis 2014-04-04 v1

Abstract

It is well-known that curvelets provide optimal approximations for so-called cartoon images which are defined as piecewise C2C^2-functions, separated by a C2C^2 singularity curve. In this paper, we consider the more general case of piecewise CβC^\beta-functions, separated by a CβC^\beta singularity curve for β(1,2]\beta \in (1,2]. We first prove a benchmark result for the possibly achievable best NN-term approximation rate for this more general signal model. Then we introduce what we call α\alpha-curvelets, which are systems that interpolate between wavelet systems on the one hand (α=1\alpha = 1) and curvelet systems on the other hand (α=12\alpha = \frac12). Our main result states that those frames achieve this optimal rate for α=1β\alpha = \frac{1}{\beta}, up to log\log-factors.

Cite

@article{arxiv.1404.1043,
  title  = {Cartoon Approximation with $\alpha$-Curvelets},
  author = {Philipp Grohs and Sandra Keiper and Gitta Kutyniok and Martin Schäfer},
  journal= {arXiv preprint arXiv:1404.1043},
  year   = {2014}
}
R2 v1 2026-06-22T03:42:38.280Z