# Multiscale texture separation

arXiv: https://arxiv.org/abs/2411.00894 · HTML: https://mlsanity.com/paper/2411.00894/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 26 references that are in the map.
- First posted on arXiv 1 Nov 2024.

## Builds on (most cited first, 1 of 1)

- [Bregman implementation of Meyer's G-norm for cartoon + textures decomposition](https://mlsanity.com/paper/2410.22777/) (2024)

## Abstract (arXiv)

In this paper, we investigate theoretically the behavior of Meyer's image cartoon + texture decomposition model. Our main results is a new theorem which shows that, by combining the decomposition model and a well chosen Littlewood-Paley filter, it is possible to extract almost perfectly a certain class of textures. This theorem leads us to the construction of a parameterless multiscale texture separation algorithm. Finally, we propose to extend this algorithm into a directional multiscale texture separation algorithm by designing a directional Littlewood-Paley filter bank. Several experiments show the efficiency of the proposed method both on synthetic and real images.