Liu Yufei, Xiao Yanhui, Tian Huawei
School of National Security, People's Public Security University of China, Beijing 100038, China.
Sensors (Basel). 2024 Dec 2;24(23):7701. doi: 10.3390/s24237701.
As a weak high-frequency signal embedded in digital images, Photo Response Non-Uniformity (PRNU) is particularly vulnerable to interference from low-frequency components during the extraction process, which affects its reliability in real-world forensic applications. Previous studies have not successfully identified the effective frequency band of PRNU, leaving low-frequency interference insufficiently suppressed and impacting PRNU's utility in scenarios such as source camera identification, image integrity verification, and identity verification. Additionally, due to differing operational mechanisms, current mainstream PRNU enhancement algorithms cannot be integrated to improve their performance further. To address these issues, we conducted a frequency-by-frequency analysis of the estimated PRNU and discovered that it predominantly resides in the frequency band above 10 Hz. Based on this finding, we propose a guided-filtering PRNU enhancement algorithm. This algorithm can function as a plug-and-play module, seamlessly integrating with existing mainstream enhancement techniques to further boost PRNU performance. Specifically, we use the PRNU components below 10 Hz as a guide image and apply guided filtering to reconstruct the low-frequency interference components. By filtering out these low-frequency components, we retain and enhance the high-frequency PRNU signal. By setting appropriate enhancement coefficients, the low-frequency interference is suppressed, and the high-frequency components are further amplified. Extensive experiments on publicly available Dresden and Daxing digital device forensics datasets confirm the efficiency and robustness of the proposed method, making it highly suitable for reliable forensic analysis in practical settings.
作为嵌入在数字图像中的微弱高频信号，光响应非均匀性（PRNU）在提取过程中特别容易受到低频分量的干扰，这影响了其在实际法医应用中的可靠性。以往的研究未能成功识别PRNU的有效频段，导致低频干扰抑制不足，影响了PRNU在源相机识别、图像完整性验证和身份验证等场景中的效用。此外，由于运行机制不同，当前主流的PRNU增强算法无法集成以进一步提高其性能。为了解决这些问题，我们对估计的PRNU进行了逐频率分析，发现它主要存在于10Hz以上的频段。基于这一发现，我们提出了一种引导滤波PRNU增强算法。该算法可以作为一个即插即用模块，与现有的主流增强技术无缝集成，以进一步提高PRNU性能。具体来说，我们将10Hz以下的PRNU分量用作引导图像，并应用引导滤波来重建低频干扰分量。通过滤除这些低频分量，我们保留并增强了高频PRNU信号。通过设置适当的增强系数，抑制了低频干扰，并进一步放大了高频分量。在公开可用的德累斯顿和大兴数字设备取证数据集上进行的大量实验证实了该方法的有效性和鲁棒性，使其非常适合在实际环境中进行可靠的法医分析。
