In-Block Prediction-Based Mixed Lossy and Lossless Reference Frame Recompression for Next-Generation Video Encoding

TLDR: A novel algorithm, which is called mixed lossy and lossless (MLL) reference frame recompression, is proposed in this paper, which differs from its previous designs and achieves a much higher compression ratio.

Abstract: Frame recompression is an efficient way to reduce the huge bandwidth of external memory for video encoder, especially for P/B frame compression. A novel algorithm, which is called mixed lossy and lossless (MLL) reference frame recompression, is proposed in this paper. The bandwidth reduction comes from two sources in our scheme, which differs from its previous designs and achieves a much higher compression ratio. First, it comes from pixel truncation. We use truncated pixels (PR) for integer motion estimation (IME) and acquire truncated residuals for factional motion estimation (FME) and motion compensation (MC). Because the pixel access of IME is much larger than FME and MC, it saves about 37.5% bandwidth under 3-b truncation. Second, embedded compression of PR helps to further reduce data. The truncated pixels in the first stage greatly help to achieve a higher compression ratio than current designs. From our experiments, 3-b truncated PR can be compressed to 15.4% of the original data size, while most current embedded compressions can only achieve around 50%. For PR compression, two methods are proposed: in-block prediction and small-value optimized variable length coding. With these experiments, the total bandwidth can be reduced to 25.5%. Our proposed MLL is hardware/software friendly and also fast IME algorithm friendly frame recompression scheme. It is more suitable to work together with the data-reuse strategy than the previous schemes, and the video quality degradation is controllable and negligible.