数字图像获取过程中会在整幅图中产生一致的噪声，而由不同图像拼接而成的图像往往会在噪声的统计特性上不一致。本文利用这一特点，提出了一种基于背景噪声分析的图像真伪被动鉴别算法。该算法利用了图像数据的高阶统计特性对背景噪声进行盲估计，并通过相邻重叠分块间的特征估计来判断图像哪些部分被篡改。实验结果表明，该方法对于鉴别拼接而成的篡改图像有显著效果。

Digital images have an inherent amount of noise typically uniform across the entire image is introduced by imags processing. So if images with different noise levels are spliced together would leave an evidence of tampering. Base on this characteristic, this paper presents a passive image forgery detection algorithm which uses blind estimation of background noise. By computing high order statistic characteristics of the background noise and estimating the neighboring overlap blocks, the algorithm could locate the forgery parts. Experiment results show its effectiveness in detecting forgery part in spliced images.