Scalable motion vector coding based on CABAL for MC-EZBC

In the scalable video coder MC-EZBC, the motion-vector (MV) bitstream was not scalable in bitrate or resolution. In this short paper, we enhance MC-EZBC with a new scalable MV coder based on context adaptive binary arithmetic coding. Alphabet general partition of MV symbols is proposed to achieve accuracy or quality scalability of MVs. A selective layered structure is used to reduce the number of MVs transmitted when appropriate, mainly needed for resolution scalability. With these two additions, we have a layered temporal, SNR, and resolution scalability for the MV bitstream. Experimentally, we find that this gives significant visual and objective improvement for low bitrates and/or resolutions with only very slight PSNR loss and unnoticeable visual loss at high bitrates.