Wyner and Ziv characterized the rate distortion function for lossy source coding with side information at the decoder. It is well known that for the quadratic Gaussian case, the Wyner-Ziv rate-distortion function coincides with the conditional rate-distortion function. In this paper, we extend the problem to the coding of multivariate Gaussian source with multiple Gaussian side information at the decoder. The achievable region is obtained, and it is easily extended to the case that the difference between the source and the side information is multivariate Gaussian, no matter what distributions the source and the side information are. We apply this theoretical model to Distributed Video Coding (DVC) by considering the difference of the Distributed frame (D frame) and the Side-information frame (S frame) to be multivariate Gaussian distributed. This introduces rate allocation problem into DVC, which can be solved by a reverse water-filling method. Simulation results show that around 1.5-2 dB coding gain benefits from the multivariate Gaussian Wyner-Ziv coding model.

The quality of the Side-information frame (S frame) influences significantly the rate-distortion performance in the Distributed Video Coding (DVC). In this letter, we propose an efficient Side-Information Frame Generator (SIFG). It considers smoothness constraints of both the motion vector field and spatial adjacent pixels. Simulation results show that the proposed techniques provide potential rate-distortion performance advantages. Besides, the fine visual quality of the S frame is obtained.