Modified distribution of correlation noise for improved Wyner-Ziv video coding performance

Abstract

Despite theorems predicting that Distributed Video Coding can achieve the same performance as traditional predictive video coding schemes, the coding efficiency of practical architectures is still far from these bounds. This is attributed to the poor Side Information (SI) estimated at the decoder and to the inability of the channel codes to recover the source at the Slepian-Wolf (SW) limits. This paper tackles the latter issue by recovering the SI bit-planes starting from the most unreliable bit of each coefficient. Most of the mismatch in SI is thus accumulated within the first decoded bit-planes, leaving the last bit-planes with very few or no mismatch. Low-Density Parity-Check Accumulate (LDPCA) codes can then benefit from such compact distribution of correlation noise since they offer a smaller percentage error, from the SW bounds, when mismatch is accumulated in few higher entropy bit-planes. Furthermore, with this setup, most of the last bit-planes can be recovered very effectively using just 8-bit or 16-bit Cyclic Redundancy Codes. Experimental results show that the proposed scheme can reduce the Wyner-Ziv bit-rates by up to 21% compared to the DISCOVER codec.