Abstract
Multiple state video coding (MSVC) is a multiple description
scheme based on frame-wise splitting of the video sequence into
two or more subsequences. Each subsequence is encoded separately
to generate descriptions which can be decoded independently. Due
to subsequence splitting, the prediction gain decreases. But since
reconstruction capabilities improve, error resilience of the
system increases. Our focus is on multiple state video coding with
unbalanced quantized descriptions, which is particularly
interesting for video streaming applications over heterogeneous
networks where path diversity is used and transmission channels
have varying transmission characteristics. The total bitrate is
kept constant, while the subsequences are quantized with different
stepsizes depending on the sequence as well as on the transmission
conditions. Our goal is to figure out under which transmission
conditions unbalanced bitstreams lead to good system performance
in terms of the average reconstructed PSNR. Besides, we
investigate the effects of intra-coding on the error resilience of
the system and show that the sequence characteristics, and in
particular the degree of motion in the sequence, have an important
impact on the decoding performance. Finally, we propose a
distortion model that is the core of an optimized rate allocation
strategy, which is dependent on the network characteristics and
status as well as on the video sequence characteristics.