Correlation noise-based unequal error protected rate-adaptive codes for distributed video coding

Abstract

Distributed video coding (DVC) is a paradigm that can shift most of the computational intensive tasks from the encoder to the decoder. This allows for the design of low complexity encoders that can be deployed in devices equipped with limited resources. However, the compression efficiency obtained using practical DVC codecs are still distant from those of traditional predictive video coding schemes such as H.264/AVC. One of the limitations of the existing DVC architectures is that they consider the correlation noise to be randomly distributed across the whole video frame. This paper shows that the Syner-Ziv (WZ) values that are closer to the endpoints of the quantization intervals have a higher probability of producing incorrect side information (SI) predictions. Thus, through this knowledge, rate-adaptive low-density parity-check accumulate codes that provide a higher level of protection to the unreliable SI bits can be exploited. Experimental results show that the proposed scheme can reduce the WZ bit-rate up to 13% relative to the state-of-the-art DISCOVER architecture when considering interpolation techniques and by up to 0.9 dB for extrapolation techniques.