Quality Analysis of Side Information Refinement in Transform-Based DVC

Distributed video coding (DVC) has been proposed for different new application domains. This rise is apparently motivated by the very attractive features of its flexibility for building very low cost video encoders and the very high built-in error resilience when applied over noisy communication channels. These features could be very effectively exploited in several application domains including wireless sensor networks for security surveillance and mobile video communications. So far DVC has used PSNR to measure the quality of the decoded video. In this paper, we analyze the performance of the DVC encoded video with three different quality matrices: PSNR, VQM and SSIM. We used one of our side information refinement algorithms in transform domain DVC as the basis for all comparisons. Simulation results show that the side information refinement technique based on motion analysis can achieve a significant coding gain with respective to all quality matrices considered. However, subjective results show that VQM has a very high correlation with the MOS which suggests that VQM is a better quality metric that can be used in DVC.