# Targeted Iterative Filtering

arXiv: https://arxiv.org/abs/2608.22299 · HTML: https://mlsanity.com/paper/2608.22299/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 17 references that are in the map.
- First posted on arXiv 23 Aug 2026.

## Built on by (most cited first, 1 of 1)

- [Mapping-Based Image Diffusion](https://mlsanity.com/paper/2608.29164/) (2026)

## Abstract (arXiv)

The assessment of image denoising results depends on the respective application area, i.e. image compression, still-image acquisition, and medical images require entirely different behavior of the applied denoising method. In this paper we propose a novel, nonlinear diffusion scheme that is derived from a linear diffusion process in a value space determined by the application. We show that application-driven linear diffusion in the transformed space compares favorably with existing nonlinear diffusion techniques.