Efficient SNR-scalability in predictive video coding

A new method is proposed for e cient SNR scalability in predictive video coding. It is of low complexity, and it is applicable to standard DCT-based video compression with motion compensation. Information that is only available to the enhancement layers is exploited to improve the quality of their frame prediction without compromising the usefulness of the compressed data provided by the base layer(s). More speci cally, the next frame prediction for use by an enhancement-layer decoder is obtained by combining, or switching between transform coe cients from: i) the reconstructed baselayer frame; and ii) the predicted enhancement-layer frame. The combining rule depends on the compressed residual of the base layer, and on the parameters used for this compression. The method is applied to standard DCT-based predictive video coding, and preliminary simulation shows consistent, substantial improvement in the performance of enhancement layers. The proposed method may be easily combined with known temporal scalability methods to provide further improvement of the performance of enhancement layers over a wide range of bit rates.