Correlation estimation for distributed wireless video communication

One important problem in distributed video coding is to estimate the variance of the correlation noise between the video signal and its decoder side information. This variance is hard to estimate due to the lack of the motion vectors at the encoder side. In this paper, we first propose a linear model to estimate this variance by referring the zero motion prediction at the encoder based on a Markov field assumption. Furthermore, not only the prediction noise from the video signal itself but also the additional noise due to wireless transmission is considered in this paper. We applied our correlation estimation method in our recent distributed wireless visual communication framework called DCAST. The experimental results show that the proposed method improves the video PSNR by 0.5-1.5dB while avoiding motion estimation at encoder.