Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Estimation of missing LSF parameters using Gaussian mixture models
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02
Efficient motion vector recovery algorithm for H.264 based on a polynomial model
IEEE Transactions on Multimedia
Video Error Concealment Using Spatio-Temporal Boundary Matching and Partial Differential Equation
IEEE Transactions on Multimedia
Temporal error concealment for MPEG coded video using a self-organizing map
IEEE Transactions on Consumer Electronics
A concealment method for video communications in an error-prone environment
IEEE Journal on Selected Areas in Communications
Cluster-based probability model and its application to image and texture processing
IEEE Transactions on Image Processing
Error concealment for video transmission with dual multiscale Markov random field modeling
IEEE Transactions on Image Processing
Nonlinear prediction for Gaussian mixture image models
IEEE Transactions on Image Processing
Recovery of image blocks using the method of alternating projections
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Packet Video Error Concealment With Gaussian Mixture Models
IEEE Transactions on Image Processing
Concealment of damaged block transform coded images using projections onto convex sets
IEEE Transactions on Image Processing
Second-order derivative-based smoothness measure for error concealment in DCT-based codecs
IEEE Transactions on Circuits and Systems for Video Technology
Model-based error concealment for wireless video
IEEE Transactions on Circuits and Systems for Video Technology
Enhanced Error Concealment With Mode Selection
IEEE Transactions on Circuits and Systems for Video Technology
XOR-based frame loss recovery scheme for video streaming
Computer Communications
Region-based error concealment of right-view frames for stereoscopic video transmission
Computers and Electrical Engineering
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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.