A joint correlation noise estimation and decoding algorithm for distributed video coding

摘要

Distributed video coding is relatively a novel video coding paradigm that enables a lower complex video encoding compared to conventional video coding schemes, at the expense of a higher-complexity decoder. Improving the rate-distortion and coding efficiency is a challenging problem in distributed video coding. Using a suitable correlation noise model along with an accurate estimation of its parameter can lead to an improved ratedistortion performance. In a distributed video codec, theWyner-Ziv frames are not available at the decoder. In addition, the correlation noise is not stationary and its statistics vary within each frame and in its corresponding transform coefficient bands. Hence, the estimation of the correlation noise model parameter is not a feasible task. In this paper, a new decoder is proposed to estimate the correlation noise parameter and carry out the decoding process progressively and recursively on an augmented factor graph. In the proposed decoder, a recursive message passing algorithm is used for decoding the bitplanes corresponding to each DCT band in a WZ frame, and simultaneously, for estimating and refining the correlation noise distribution parameter. To approximate the posterior distribution of the correlation noise parameter, and consequently, derive a closed-form expression for the messages on the augmented factor graph, a variational Bayes algorithm is employed. Extensive simulations are carried out to show that using the proposed decoder leads to considerable improvement in the rate-distortion performance of the distributed video codec, particularly on video sequences with fast motions.