On the application of multivariate kernel density estimation to image error concealment

This paper proposes a methodology for the application of multivariate kernel density estimation (KDE) to MMSE-based image/video error concealment (EC). We show that the estimation of the kernel bandwidth matrix for EC must follow a criterion different from that of typical KDE problems. In particular, we propose a bandwidth built as the product of a structure matrix and a scale factor obtained with a minimum square error criterion. We show that our proposal can achieve average PSNR improvements larger than 1 dB with respect to other state-of-the-art techniques.