Dual-Stream Image Sharing Chain Detection via Dynamic Information Compensation

IF 3.2 2区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Signal Processing Letters Pub Date : 2025-03-11 DOI:10.1109/LSP.2025.3550282

Xinyi Su;Yuanman Li;Yulong Zheng;Xia Li

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引用次数: 0

Abstract

Image Sharing Chain Detection (ISCD) aims to reconstruct the complete trajectory of an image's dissemination across social platforms and is an important task in multimedia forensics. Current methods using DCT histograms are insufficient in uncovering platform compression traces and exhibit limitations in detecting weak trace platforms. In this letter, we propose an innovative dual-stream ISCD framework via dynamic information compensation. This framework integrates features from both the frequency domain and the residual domain to extract compression characteristics. Unlike existing methods, we employ binary stereo DCT in the frequency domain to focus on the spatiality of compression operations. Additionally, we design a dynamic information compensation mechanism to enhance platform traces by storing compensation fingerprints of the sharing chains. Furthermore, we develop a new dataset, F-4OSN-SC, encompassing 4 platforms to simulate more realistic social networking scenarios. Experimental results demonstrate that our model outperforms existing methods across multiple datasets.

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基于动态信息补偿的双流图像共享链检测

图像共享链检测（ISCD）旨在重建图像在社交平台上传播的完整轨迹，是多媒体取证中的一项重要任务。目前使用DCT直方图的方法在发现平台压缩痕迹方面不足，并且在检测弱痕迹平台方面表现出局限性。在这封信中，我们提出了一个创新的双流ISCD框架，通过动态信息补偿。该框架结合频域和残差域的特征提取压缩特征。与现有方法不同，我们在频域使用二进制立体DCT来关注压缩操作的空间性。此外，我们设计了一种动态信息补偿机制，通过存储共享链的补偿指纹来增强平台痕迹。此外，我们开发了一个新的数据集F-4OSN-SC，包含4个平台来模拟更现实的社交网络场景。实验结果表明，我们的模型在多数据集上优于现有的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Signal Processing Letters 工程技术-工程：电子与电气

CiteScore

7.40

自引率

12.80%

发文量

339

审稿时长

2.8 months

期刊介绍： The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing. Papers published in the Letters can be presented within one year of their appearance in signal processing conferences such as ICASSP, GlobalSIP and ICIP, and also in several workshop organized by the Signal Processing Society.