# Scalable Kernel-Based Minimum Mean Square Error Estimator for Accelerated Image Error Concealment

arXiv: https://arxiv.org/abs/2205.11226 · HTML: https://mlsanity.com/paper/2205.11226/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 44 references that are in the map.
- First posted on arXiv 23 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)

Error concealment is of great importance for block-based video systems, such as DVB or video streaming services. In this paper, we propose a novel scalable spatial error concealment algorithm that aims at obtaining high quality reconstructions with reduced computational burden. The proposed technique exploits the excellent reconstructing abilities of the kernel-based minimum mean square error K-MMSE estimator. We propose to decompose this approach into a set of hierarchically stacked layers. The first layer performs the basic reconstruction that the subsequent layers can eventually refine. In addition, we design a layer management mechanism, based on profiles, that dynamically adapts the use of higher layers to the visual complexity of the area being reconstructed. The proposed technique outperforms other state-of-the-art algorithms and produces high quality reconstructions, equivalent to K-MMSE, while requiring around one tenth of its computational time.