Adaptation for scalable video coding is one of the recent challenges in video distribution over modern networks, which are heterogeneous both in terms of available bandwidth and user end terminal capability. In case of SNR/spatial combined scalability an interesting issue concerns how to remove data from different spatial resolutions for the adaptation to different rates. Scalable Video Coding offers the possibility to adapt the content following the “quality layer” abstraction. In this work we present a new method to optimally define quality layers for a scalable bitstream in a combined scalability scenario using Integer Linear Programming and distortion models. The performance of the proposed approach are comparable with the state-of-the-art methods, but they are obtained with a significant complexity reduction and augmented flexibility.

Optimal Rate Adaptation in the Scalable Extension of H264/AVC with Combined Scalability

LIMA, LIVIO
Membro del Collaboration Group
;
MAURO, Massimo
Membro del Collaboration Group
;
LEONARDI, Riccardo
Supervision
2011-01-01

Abstract

Adaptation for scalable video coding is one of the recent challenges in video distribution over modern networks, which are heterogeneous both in terms of available bandwidth and user end terminal capability. In case of SNR/spatial combined scalability an interesting issue concerns how to remove data from different spatial resolutions for the adaptation to different rates. Scalable Video Coding offers the possibility to adapt the content following the “quality layer” abstraction. In this work we present a new method to optimally define quality layers for a scalable bitstream in a combined scalability scenario using Integer Linear Programming and distortion models. The performance of the proposed approach are comparable with the state-of-the-art methods, but they are obtained with a significant complexity reduction and augmented flexibility.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/98112
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