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Summary
To enable video transmission
over heterogeneous wireless networks, a highly scalable compression and
streaming framework that can adapt to large and rapid bandwidth variations
in realtime is necessary. MPEG-4 Fine Grained Scalability (FGS) provides
fine-grained SNR and temporal scalabilities, but these scalabilities are
implemented and performed independently, thereby neglecting the gains
that can be made from making joint SNR-temporal decisions to maximize
quality. In this paper, a novel Fine Grained SNR-Temporal scalability
framework called FGS+ that provides a new level of erformance by considering
SNR and temporal scalability jointly is presented. This new solution uses
the results of our subjective tests, which indicate the levels to which
SNR-quality needs to be enhanced before motion-smoothness should be improved.
The study also reveals that these SNRtemporal tradeoff points vary among
videos, and depend on the characteristics of the video. Based on these
observations, our solution uses reference frames, enhanced relative to
FGS, for prediction, improving visual quality over MPEG-4 FGS by up to
1.5 dB.
People
Raj Kumar Rajendran
Professor Mihaela
van der Schaar
Professor Shih-Fu
Chang
Publication
R. Kumar Rajendran,
M. van der Schaar, S.-F. Chang, FGS+: Optimizing the Joint Spatio-Temporal
Video Quality in MPEG-4 Fine Grained Scalable Coding, IEEE International
Symposium on Circuits and Systems (ISCAS 2002), Phoenix, Arizona, May
2002.
(PS.GZ/PDF)
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