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arXiv · 2205.11226

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

Ján Koloda·Jürgen Seiler·Antonio M. Peinado·André Kaup
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Abstract

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.

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Ján Koloda, Jürgen Seiler, Antonio M. Peinado, André Kaup. 2022-05-23. Scalable Kernel-Based Minimum Mean Square Error Estimator for Accelerated Image Error Concealment. https://doi.org/10.1109/tbc.2016.2619581

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