Koloda J, Seiler J, Peinado A, Kaup A (2017)
Publication Language: English
Publication Type: Journal article
Publication year: 2017
Book Volume: 63
Pages Range: 59-70
Journal Issue: 1
Error concealment (EC) is of great importance for block-based video systems, such as digital video broadcasting or video streaming services. In this paper, we propose a novel scalable spatial EC 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.
APA:
Koloda, J., Seiler, J., Peinado, A., & Kaup, A. (2017). Scalable Kernel-Based Minimum Mean Square Error Estimator for Accelerated Image Error Concealment. IEEE Transactions on Broadcasting, 63(1), 59-70. https://dx.doi.org/10.1109/TBC.2016.2619581
MLA:
Koloda, Jan, et al. "Scalable Kernel-Based Minimum Mean Square Error Estimator for Accelerated Image Error Concealment." IEEE Transactions on Broadcasting 63.1 (2017): 59-70.
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