分布式视频编码中相关噪声分布的非参数估计方法研究

针对分布式视频编码系统中相关噪声（Correlation Noise, CN）分布难以准确模拟的问题，根据CN分布的特点，提出CN的非参数估计方法，建立了基于最优窗宽的核密度估计-均匀分布模型(Kernel Density Estimation-Uniform Distribution Model, KDEUDM)，比较了变换域Wyner-Ziv（Transform Domain Wyner-Ziv, TDWZ）系统中CN的参数估计法和非参数估计法所建立的噪声模型对系统性能的影响。实验结果表明，非参数估计方法能较准确地模拟CN的分布，与参数估计法相比，用非参数估计法建立的噪声模型能使WZ帧编码在高码率下最高能节约10%的码率。

Research on non-parametric estimation for correlation noise distribution in distributed video coding

Since it is difficult to estimate the correlation noise distribution, non-parametric estimation method for correlation noise is proposed according to the feature of correlation noise. Kernel density estimation-uniform distribution model based on optimal bandwidth is proposed. The impact of noise model using parameter estimation method and non-parametric estimation method on the system performance in transform domain Wyner-Ziv system is compared. The experiments results show that non-parametric estimation method can simulate correlation noise distribution and the established noise model using non-parametric estimation method can save rate about 10% at most at high bit rate for WZ frame.