Department of Information Engineering, University of Florence, Via di S. Marta, 3, 50139 Florence, Italy.
Department of Electronic Media, Saudi Electronic University, Abi Bakr As Sadiq Rd, Riyadh 11673, Saudi Arabia.
Sensors (Basel). 2018 Nov 6;18(11):3801. doi: 10.3390/s18113801.
Digital source identification is one of the most important problems in the field of multimedia forensics. While Standard Dynamic Range (SDR) images are commonly analyzed, High Dynamic Range (HDR) images are a less common research subject, which leaves space for further analysis. In this paper, we present a novel database of HDR and SDR images captured in different conditions, including various capturing motions, scenes and devices. As a possible application of this dataset, the performance of the well-known reference pattern noise-based source identification algorithm was tested on both kinds of images. Results have shown difficulties in source identification conducted on HDR images, due to their complexity and wider dynamic range. It is concluded that capturing conditions and devices themselves can have an impact on source identification, thus leaving space for more research in this field.
数字源识别是多媒体取证领域中最重要的问题之一。虽然标准动态范围 (SDR) 图像是常见的分析对象，但高动态范围 (HDR) 图像是一个较少研究的课题，这为进一步分析留下了空间。在本文中，我们提出了一个新的 HDR 和 SDR 图像数据库，这些图像是在不同条件下拍摄的，包括各种拍摄动作、场景和设备。作为该数据集的一个可能应用，我们对基于著名参考模式噪声的源识别算法在这两种类型的图像上的性能进行了测试。结果表明，由于 HDR 图像的复杂性和更宽的动态范围，对其进行源识别存在困难。结论是，拍摄条件和设备本身可能会对源识别产生影响，因此该领域还有更多的研究空间。
