| Abstract |
This paper contains two contributions to very-low-bitrate video coding.
First, we show that in contrast to common practice incremental techniques
for rate-distortion optimization such as the generalized BFOS algorithm may
clearly outperform the standard technique based on Lagrangian multipliers.
This is relevant in cases where the computation of RD-points has a low
complexity. Second, we report on recent progress of our ongoing research
evaluating the prospects of adaptive vector quantization (AVQ) for verylow-
bitrate video coding. In contrast to conventional state-of-the-art video
coding based on entropy coding of motion compensated residual frames in
the frequency domain, adaptive vector quantization offers the potential to
adapt its codebooks to the changing statistics of image sequences. The basic
building blocks of our current AVQ video codec are (1) block-based coding
in the wavelet domain where wavelet coefficients correspond to (overlapping)
spatial regions, (2) hierarchical organization of the wavelet coef-
ficients using quad-tree structures, (3) three way coding mode decision for
each block (block replenishment, product code vector quantization, new VQ
block with codebook update), and (4) rigorous rate/distortion optimization
for all coding choices (image partition and block coding mode). This video
codec does not apply motion compensation, however. A comparison with
standard transform coding (H.263) shows that inspite of the improvements
of our coder over previously published AVQ video coders it still shows a
performance gap of about 1 dB for some test sequences. We conclude that motion compensation is essential also for codecs based on AVQ. First preliminary
tests show that AVQ coders that incorporate motion compensation can become competitive with standard transform coding. |