Adaptive double-phase Rudin--Osher--Fatemi denoising model

Wojciech Górny, Michał Łasica, Alexandros Matsoukas
10/5/2025
eess.IVcs.CVmath.NA

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Abstract

We propose a new image denoising model based on a variable-growth total variation regularization of double-phase type with adaptive weight. It is designed to reduce staircasing with respect to the classical Rudin--Osher--Fatemi model, while preserving the edges of the image in a similar fashion. We implement the model and test its performance on synthetic and natural images in 1D and 2D over a range of noise levels.

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Cite this paper

@article{grny2025adaptive,
  title  = {Adaptive double-phase Rudin--Osher--Fatemi denoising model},
  author = {Wojciech Górny and Michał Łasica and Alexandros Matsoukas},
  year   = {2025},
  eprint = {2510.04382},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2510.04382v1}
}

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