Correlation noise model for transform domain Wyner-Ziv video coding

In Wyner-Ziv (WZ) video coding, the coding efficiency depends critically on the correlation noise model between the original Wyner-Ziv frame data and its side information. The given literatures always approximate the probability distributions of the correlation noise with zero-mean Laplacian distribution. Based on study of the residual distribution between the original data and its side information in the transform domain, it is found that DC coefficient band does not accord with zero-mean Laplacian distribution, the error distribution of coefficient bands is neither temporally nor spatially stationary. According to the characteristics of residual coefficients in the transform domain, an efficient correlation noise model and an adaptive parameter estimation algorithm are proposed at the decoder for the transform domain WZ video coding. Experimental results show that the proposed algorithm can effectively improve the coding efficiency.