Successive refinement based Wyner-Ziv video compression

Wyner-Ziv coding enables low complexity video encoding with the motion estimation procedure shifted to the decoder. However, the accuracy of decoder motion estimation is often low, due to the absence of the input source frame (at the decoder). In this paper, we propose a novel Wyner-Ziv successive refinement approach to improve the motion compensation accuracy and the overall compression efficiency of Wyner-Ziv video coding. Our approach encodes each frame by multiple Wyner-Ziv coding layers and uses the progressively refined reconstruction frame to guide the motion estimation for progressively improved accuracy. The proposed approach yields competitive results against state-of-the-art low complexity Wyner-Ziv video coding approaches, and can gain up to 3.8dB over the conventional Wyner-Ziv video coding approach and up to 1.5dB over the previous bitplane-based refinement approach. Furthermore, this paper also presents the rate distortion analysis and the performance comparison of the proposed approach and conventional approaches. The rate distortion performance loss (due to performing decoder motion estimation) is at most 2.17dB (or equivalently 1/4 nats/pixel) in our scheme according to our analysis, but can be more than 6dB in the conventional approach according to previous research. For the simplified two-layers case of our approach, we derive the optimal subsampling ratio in the sense of rate distortion performance. We also extend our analysis and conclusions from P frame to B frame. Finally, we verify our analysis by experimental results.