分布式视频编码（DVC）是建立在Wyner-Ziv(WZ)有损源编码理论基础上的全新视频编码框架，具有编码复杂度低、抗误码性能好的特点。普通的DVC在解码端用插值的方法构造边信息时会丢失部分信息，提出了从用于插值边信息的前后帧中提取特征并预测重构帧的下一个比特值，并利用预测的比特值修改重构概率密度函数。实验结果表明，该方法能在传输较少比特平面时提高重构帧的PSNR和主观质量。

Distributed video coding(DVC)is a new paradigm for video compression, based on Wyner-Ziv’s lossy source coding theory. DVC features low-complexity video encoding and is robust against transmission errors. Common DVC loses information during the side information(SI)interpolation at the decoder. In this paper, we extract features from the adjacent frames which are used to interpolate the SI so as to predict the next bit of the reconstructed frame. The predicted bit is used to modify the probability density function(PDF)of reconstruction. The experimental results show that our method achieves higher PSNR and better subjective effects than other methods even when fewer bit planes are transmitted.