Scalable wavelet video coding using aliasing-reduced hierarchical motion compensation

We describe a spatially scalable video coding framework in which motion correspondences between successive video frames are exploited in the wavelet transform domain. The basic motivation for our coder is that motion fields are typically smooth and, therefore, can be efficiently captured through a multiresolutional framework. A wavelet decomposition is applied to each video frame and the coefficients at each level are predicted from the coarser level through backward motion compensation. To remove the aliasing effects caused by downsampling in the transform, a special interpolation filter is designed with the weighted aliasing energy as part of the optimization goal, and motion estimation is carried out with lowpass filtering and interpolation in the estimation loop. Further, to achieve robust motion estimation against quantization noise, we propose a novel backward/forward hybrid motion compensation scheme, and a tree structured dynamic programming algorithm to optimize the backward/forward mode choices. A novel adaptive quantization scheme is applied to code the motion predicted residue wavelet coefficients. Experimental results reveal 0.3–2-dB increase in coded PSNR at low bit rates over the state-of-the-art H.263 standard with all enhancement modes enabled, and similar improvements over MPEG-2 at high bit rates, with a considerable improvement in subjective reconstruction quality, while simultaneously supporting a scalable representation.