Measurement Compression in Compressive Sampling Based Distributed Video Coding

Compressive sampling (CS) theory and distributed video coding (DVC) are two techniques suitable to scenarios where a video codec with simple encoder and complex decoder is desired. The combination of CS theory and DVC is a new research trend in this field and several integrated schemes have now appeared. However, in these existing integrated schemes, the dependencies between measurements of successive image frames have not yet been exploited. Recently we proposed a Gaussian distribution model to describe the correlations of measurements between a CS frame and its side information in a previous paper. In this paper, we extend the Gaussian model to correlations of measurements between two successive key frames. Based on this model the measurements of key frame can be compressed using a channel coder, similar to that in DVC. Experiment results indicate that the measurement compression ratio of the proposed compression scheme achieves 48.96% -88.12% for key frames when measurement rate of key frame is 50%.