In Distributed Video Coding (DVC), compression is achieved by exploiting correlation between frames at the decoder, instead of at the encoder. More specifically, the decoder uses already decoded frames to generate side information Y for each Wyner-Ziv frame X, and corrects errors in Y using error correcting bits received from the encoder. For efficient use of these bits, the decoder needs information about the correlation between X available at the encoder and Y at the decoder. While several techniques for online estimation of correlation noise X − Y have been proposed, the quantization noise in Y has not been taken into account.As a solution, in this paper, we calculate the quantization noise of intra frames at the encoder and use this information at the decoder to improve the accuracy of the correlation noise estimation. Results indicate average Wyner-Ziv bit rate reductions up to 19.5% (Bjøntegaard delta) for coarse quantization.

Distributed video coding (DVC) features simple encoders but complex decoders, which lies in contrast to conventional video compression solutions such as H.264/AVC. This shift in complexity is realized by performing motion estimation at the decoder side instead of at the encoder, which brings a number of problems that need to be dealt with. One of these problems is that, while employing different coding modes yields significant coding gains in classical video compression systems, it is still difficult to fully exploit this in DVC without increasing the complexity at the encoder side. Therefore, in this paper, instead of using an encoder-side approach, techniques for decoder-side mode decision are proposed. A rate-distortion model is derived that takes into account the position of the side information in the quantization bin. This model is then used to perform mode decision at the coefficient level and bitplane level. Average rate gains of 13 to 28% over the state-ofthe-art DISCOVER codec are reported, for a GOP of size four, for several test sequences.

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