Athanasios Leontaris | PubMed Health

PubMed2006

Drift-resistant SNR scalable video coding.

We address the problem of enhancement layer drift estimation for fine granular scalable video. An optimal per-pixel drift estimation algorithm is introduced. The encoder assumes that there is some truncation of the enhancement layer, which does not allow the enhancement layer reference to be properly reconstructed, and the encoder recursively estimates the associated drift and chooses coding modes accordingly. The approach yields performance gains of about 1 dB across low to medium rates. In addition, we investigate dual frame prediction, for both base and enhancement layer, with pulsed-quality allocation in the base

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PubMed2004

Video compression for lossy packet networks with mode switching and a dual-frame buffer.

Video codecs that use motion compensation benefit greatly from the development of algorithms for near-optimal intra/inter mode switching within a rate-distortion framework. A separate development has involved the use of multiple-frame prediction, in which more than one past reference frame is available for motion estimation. In this paper, we show that using a dual-frame buffer (one short-term frame and one long-term frame available for prediction) together with intra/inter mode switching improves the compression performance of the coder. We improve the mode-switching algorithm with the use of half-pel motion vectors. In addition, we investigate the effect of feedback in making more informed and effective mode-switching decisions. Feedback information is used to limit drift errors due to packet losses by synchronizing the long-term frame buffers of both the encoder and the decoder.

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