Source Distortion Estimation for Wyner-Ziv Distributed Video Coding

Abstract

Distributed video coding (DVC), which can move the computational complexity burden from the encoder to the decoder, is an effective source coding paradigm for promising video applications over wireless networks, e.g. wireless video surveillance and wireless video sensor networks. For these video applications, it is crucial to provide an efficient way to assess the quality of reconstructed videos accurately. However, due to absence of original frames at the decoder, how to estimate the reconstructed video quality of DVC remains a challenging task. In this paper, we propose a source distortion estimation method for DVC, in which the distortion incurred by the quantization and reconstruction is taken into account. Focusing on the statistical distortion of a transformed coefficient in each Wyner-Ziv (WZ) frame, the proposed method measures the average distortion of WZ frames utilizing only the coding information available at the decoder, i.e. the coefficients of side information (SI) frames and the decoded coefficients outputted from a decoder of low density parity code (LDPC). Besides, we propose an estimation algorithm of probability distribution parameters to deal with the case that all the coefficients of a sub-band are zero values by using an approximate principle. Experiments have been conducted to validate the accuracy of our estimation method. For no requirement of original WZ frames at the decoder, the presented method can be suitable for real-time video applications.