Mixture Model- and Least Squares-Based Packet Video Error Concealment
Artikel i vetenskaplig tidskrift, 2009

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 infinity. There are also drawbacks, however. The estimator has high online computational complexity, 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 computation-performance tradeoff.

projections

spatio-temporal error concealment

adaptive sparse reconstructions

least

squares (LS) estimation

image recovery

Block-based packet video

em

maximum-likelihood

algorithm

transmission

Författare

Daniel Persson

Chalmers, Signaler och system, Kommunikationssystem, informationsteori och antenner, Kommunikationssystem

Thomas Eriksson

Chalmers, Signaler och system, Kommunikationssystem, informationsteori och antenner, Kommunikationssystem

IEEE Transactions on Image Processing

1057-7149 (ISSN)

Vol. 18 5 1048-1054

Ämneskategorier

Signalbehandling

DOI

10.1109/TIP.2009.2014261