Abstract
In this paper we propose a new H.264 SVC transrating architecture for spatially scalable SVC compressed video streams. The algorithm is low complexity based, it applies to spatially scalable pre-encoded video streams and allows fine bit rate granularity while keeping highest spatial resolution. Simulation results demonstrate that transcoded bit streams produce satisfying picture quality even at bit rate reduction up to 66%. The comparison with MGS compressed video streams shows that the proposed transrating aslgorithm offers satisfying performances compared to MGS when bit rate reduction remains limited. Moreover quality scalability is obtained thanks to our algorithm even if the SVC compressed video bitstream has not been processed using MGS scalability right from the start.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-319-02895-8_64
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Deknudt, C., Coudoux, FX., Corlay, P., Gazalet, M., Gharbi, M. (2013). Efficient Low Complexity SVC Video Transrater with Spatial Scalability. In: Blanc-Talon, J., Kasinski, A., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2013. Lecture Notes in Computer Science, vol 8192. Springer, Cham. https://doi.org/10.1007/978-3-319-02895-8_1
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DOI: https://doi.org/10.1007/978-3-319-02895-8_1
Publisher Name: Springer, Cham
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