Mixture Model- and Least Squares-Based Packet Video Error
A Gaussian mixture model (GMM)-based spatio-temporal error concealment
approach has recently been proposed for packet video. The method improves
peak signal-to-noise ratio (PSNR) compared
to several famous error concealment methods, and it
is asymptotically optimal when the number of mixture components goes to
There are also drawbacks however. The estimator has high online
which implies that fewer surrounding pixels to the lost area than desired
are used for
error concealment. Moreover, GMM parameters are estimated without
considering maximization of the
error concealment PSNR.
In this paper we propose a mixture-based estimator and a least squares
approach for solving the spatio-temporal error concealment problem.
Compared to the GMM scheme, the new method may base error concealment on
more surrounding pixels to the loss, while maintaining low computational
complexity, and model parameters are found
by an algorithm that increases PSNR in each iteration.
The proposed method outperforms the GMM-based scheme in terms of