# Frequency selective extrapolation with residual filtering for image error concealment

arXiv: https://arxiv.org/abs/2205.07476 · HTML: https://mlsanity.com/paper/2205.07476/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 11 references that are in the map.
- First posted on arXiv 16 May 2022.

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

- [Complex-Valued Frequency Selective Extrapolation for Fast Image and Video Signal Extrapolation](https://mlsanity.com/paper/2204.14193/) (2022)

## Abstract (arXiv)

The purpose of signal extrapolation is to estimate unknown signal parts from known samples. This task is especially important for error concealment in image and video communication. For obtaining a high quality reconstruction, assumptions have to be made about the underlying signal in order to solve this underdetermined problem. Among existent reconstruction algorithms, frequency selective extrapolation (FSE) achieves high performance by assuming that image signals can be sparsely represented in the frequency domain. However, FSE does not take into account the low-pass behaviour of natural images. In this paper, we propose a modified FSE that takes this prior knowledge into account for the modelling, yielding significant PSNR gains.