针对传感器模式噪声易受CFA插值噪声和JPEG压缩噪声污染，提出一种基于空域平滑滤波的传感器模式噪声预处理方法，去除干扰噪声，从而提高数字照片图像来源检测准确率.假设传感器模式噪声是一种类似高斯白噪声的随机信号，其在频域具有与高斯白噪声相似的平坦频谱; 基于此，在空域采用高斯白噪声对传感器模式噪声进行引导滤波，其空域平滑效果使传感器模式噪声在保持自身性质的同时，拥有与高斯白噪声相似的特性.手机相机照片图像库的评估实验结果表明，与现有预处理方法相比，所提算法在图像来源检测准确度上Kappa统计系数提高了0.026以上，同时算法对JPEG压缩的鲁棒性也明显优于其他算法.

The Sensor Pattern Noise (SPN) is easily contaminated by CFA interpolation noise and JPEG compression noise. These unwanted artifacts may result in false identifications in SPN-based source camera detection. A preprocessing method of SPN based on spatial smoothing was proposed in order to improve the accuracy of source camera detection. It is assumed that the SPN is a random signal similar to white Gaussian noise (WGN), and has a flat frequency spectrum similar to that of WGN in the frequency domain. Based on this assumption, WGN-guided filtering was used in the spatial domain in the proposed method. The spatial smoothing effect can suppress the unwanted artifacts of the SPN. At the same time, the SPN can maintain its own properties and possess similar characteristics with WGN. The proposed method was evaluated on our own database of camera images from cellphones. The experimental results show that the proposed method outperforms the existing preprocessing methods, the accuracy of the source camera detection being increased by more than 0.026 in terms of the Kappa statistical coefficients. The robustness to JPEG compression of the proposed method is also better than others.