在利用数字图像与数码相机的噪声相关性来鉴别数字图像来源的实验中，发现噪声相关性有对称和非对称两种分布。为了提高鉴别数字图像来源的正确性，正确设置判别阈值，针对噪声相关性的非对称分布，在(0,1］区间构造了一个广义chi平方分布的新函数，并提出了一种利用广义chi平方分布来描述噪声相关性的非对称分布和利用广义高斯分布来描述噪声相关性的对称分布的新方法。实验结果表明，该方法与仅采用一个广义高斯分布的方法相比，可以使鉴别错误率降低38%以上，可见利用不同的概率密度函数来描述相应的分布是减小鉴别错误率的一个有效途径。

The symmetrical and asymmetrical distribution of noise correlation between digital image and digital camera are discovered in the experiment of identifing digital image origin by noise correlation. In order to improve the validity of identifi cation of digital image origin and predetermine accurately threshold of identification, a new probability density function of generalized chi square distribution is constructed within (0,1］ for asymmetrical distribution of noise correlation. A new method is proposed to apply generalized chi square distribution to describe the asymmetrical distributions of noise correlation, and using generalized Gaussian distribution to describe the symmetrical distributions of noise correlation. The experiment shows that the new method can reduce over 38% of the false rate compared with the method of generalized Gaussian distribution , consequently, it is an effective approach to reduce the false rate by diverse probability density functions to describe different distributions of noise correlation.