This paper explores content-based image registration as a means of dealing with and understanding better Electronic Image Stabilization (EIS) in the context of Photo Response Non-Uniformity (PRNU) alignment. A novel and robust solution to extrapolate the transformation relating the different image output formats for a given device model is proposed. This general approach can be adapted to specifically extract the scale factor (and, when appropriate, the translation) so as to align native resolution images to video frames, with or without EIS on, and proceed to compare PRNU patterns. Comparative evaluations show that the proposed approach outperforms those based on brute-force and particle swarm optimization in terms of reliability, accuracy and speed. Furthermore, a tracking system able to revert back EIS in controlled environments is designed. This allows one to investigate the differences between the existing EIS implementations. The additional knowledge thus acquired can be exploited and integrated in order to design and implement better future PRNU pattern alignment methods, aware of EIS and suitable for video source identification in multimedia forensics applications.

本文探讨了基于内容的图像配准，以此作为在光响应非均匀性（PRNU）对齐的情况下更好地处理和理解电子图像稳定（EIS）的一种方法。提出了一种新颖且鲁棒的解决方案，可以针对给定的设备模型外推涉及不同图像输出格式的转换。这种通用方法可以适用于专门提取比例因子（并在适当时转换），以便在启用或不启用EIS的情况下将原始分辨率图像与视频帧对齐，然后继续比较PRNU模式。比较评估表明，该方法在可靠性，准确性和速度方面均优于基于蛮力和粒子群优化的方法。此外，设计了一种能够在受控环境中还原EIS的跟踪系统。这样一来，您可以调查现有EIS实现之间的差异。这样获得的额外知识可以被利用和整合，以设计和实现更好的未来PRNU模式对齐方法，了解EIS并适用于多媒体取证应用中的视频源识别。