Hierarchical image resampling detection based on blind deconvolution |
| |
| Affiliation: | 1. School of Electronic Information Engineering, Tianjin University, Tianjin, China;2. School of Electrical Engineering and Information, Southwest Petroleum University, Chengdu, China;1. Department of Computer Science and Information Engineering, National Dong Hwa University, Taiwan;2. Department of Computer Science, Jinan University, Guangzhou, China;3. Nanjing University of Information Science & Technology, Nanjing, China;4. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China;1. Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava, Slovakia;2. STU Centre for Nanodiagnostics, Vazovova 5, 812 43 Bratislava, Slovakia;1. School of Computer and Information, Hefei University of Technology, Hefei, China;2. School of Information Engineering, Wuhan University of Technology, Wuhan, China;3. Huazhong University of Science and Technology, Wuhan, China;1. Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China;2. Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing 211166, China;3. Department of Bioinformatics, School of Basic Medical Sciences, Nanjing Medical University, Nanjing 211116, China;1. Department of Pancreato-Biliary Surgery, The First Affiliated Hospital of Sun Yat-Sen University, No. 58, Zhongshan Road 2, Guangzhou, 510080, PR China;2. General Surgical Laboratory, The First Affiliated Hospital of Sun Yat-Sen University, No. 58, Zhongshan Road 2, Guangzhou, 510080, PR China;3. Department of Laboratory, The First Affiliated Hospital of Sun Yat-Sen University, No. 58, Zhongshan Road 2, Guangzhou, 510080, PR China;4. Department of Hepatic Surgery, The First Affiliated Hospital of Sun Yat-Sen University, No. 58, Zhongshan Road 2, Guangzhou, 510080, PR China;5. Animal Center, The First Affiliated Hospital of Sun Yat-Sen University, No. 58, Zhongshan Road 2, Guangzhou, 510080, PR China |
| |
| Abstract: | Resampling detection is a helpful tool in multimedia forensics; however, it is a challenge task in cases with compression and noisy. In this paper, by modeling the recovery of edited images using an inverse filtering process, we propose a novel resampling detection framework based on blind deconvolution. Different interpolation types in the resampling process can be distinguished by our algorithm, which is significant for practical forensics scenarios. Furthermore, in contrast to traditional resampling detection algorithms, our method can effectively avoid interference caused by JPEG block artifacts. As the experimental results show, our method is more robust than other state-of-the-art approaches in the case of strong JPEG compression and substantial Gaussian noise. |
| |
| Keywords: | Image forensics Image resampling detection Blind deconvolution |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
