An efficient SNR scalability coding framework hybrid open-close loop FGS coding

This paper presents a novel high-efficient hybrid open-close loop based fine granularity scalable (HOCFGS) coding framework supporting different decoding complexity applications. The open-loop motion compensation for inter-pictures is introduced to efficiently exploit the temporal correlation among adjacent pictures for both base layer and FGS enhancement layer within a wide bit-rate range. An efficient rate-distortion optimized macro-block mode decision rule is used to reduce drifting error and achieve comparable coding performance at the lowest bit-rate point (base layer) with non-scalable coding. An approach like MPEG-4 FGS coding with close-loop motion compensation only at base layer is used for some inter-pictures to stop the drifting error propagation. Furthermore, to achieve better coding performance for these inter-pictures, block based progressive fine granularity scalable (BLPFGS) is introduced, in which leaky prediction is used to generate high-quality reference for FGS enhancement layer. In BLPFGS coding, efficient bit-plane coding and de-blocking techniques are investigated to improve the coding performance for FGS enhancement layer, especially at low bit-rate points. The coding performance for the proposed method is verified by integrating it into MPEG SVC reference software