A Gaussian Process Regression Framework for Spatial Error Concealment with Adaptive Kernels

We have developed a Gaussian Process Regression method with adaptive kernels for concealment of the missing macro-blocks of block-based video compres-sion schemes in a packet video system. Despite promis-ing results, the proposed algorithm introduces a solid framework for further improvements. In this paper, the problem of estimating lost macro-blocks will be solved by estimating the proper covariance function of the Gaussian process defined over a region around the missing macro-blocks (i.e. its kernel function). In or-der to preserve block edges, the kernel is constructed adaptively by using the local edge related information. Moreover, we can achieve more improvements by local estimation of the kernel parameters. While restoring the prominent edges of the missing macro-blocks, the pro-posed method produces perceptually smooth concealed frames. Objective and subjective evaluations verify the effectiveness of the proposed method. 1