  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.
