Hash-Based Motion Modeling in Wyner-Ziv Video Coding
Generally, distributed video coding (DVC) schemes perform motion estimation at the decoder side, without the current frame being available. In order to generate the side-information reliably, one solution consists in allocating a limited bit budget to send a hash of the current frame. At the decoder, this auxiliary hash is used to perform motion estimation. This paper studies the accuracy of hash-based motion estimation and compares it to conventional encoder-side motion estimation. We show that, at low rates, the very limited bit-budget of the hash does not ensure a reliable motion estimation, while at medium to high rates the motion accuracy is comparable with the finite precision used to represent motion vectors. Then, we derive the rate-distortion characteristic, which combines the cost of encoding the hash and the prediction residuals after decoder-side motion compensation. We show that, at high rates, hash-based motion modeling can virtually achieve the same coding efficiency as motion-compensated predictive coding. Instead, at medium-to-low rates we observe a significant coding loss. Experimental results on real video sequences validate the results of the proposed model.