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Titlebook: Digital Forensics and Watermarking; 17th International W Chang D. Yoo,Yun-Qing Shi,Gwangsu Kim Conference proceedings 2019 Springer Nature

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發(fā)表于 2025-3-28 14:43:52 | 只看該作者
Comparison of DCT and Gabor Filters in Residual Extraction of CNN Based JPEG Steganalysisrnable. It’s different from the conventional steganalysis method where Gabor filters have advantages over DCT filters. When the parameters of the pre-processing filters are learnable, both Gabor filter and DCT filter can achieve better performance compared with the condition where the parameters are
42#
發(fā)表于 2025-3-28 18:50:42 | 只看該作者
Traitor Tracing After Visible Watermark Removallts prove that the watermark can be detected as long as the quality of the watermarked video is not significantly reduced, especially if the originally-distributed watermarked video has a high quality. Moreover, the watermark should be embedded into a video with sufficient motion. In conclusion, the
43#
發(fā)表于 2025-3-28 23:30:12 | 只看該作者
Reversible Data Hiding in Encrypted Images Based on Image Partition and Spatial Correlationly PEE and MHM to embed the LSB of . to reserve space for secret data. Next, we encrypt the image and change the LSB of . to realize the embedding of secret data. In the process of extraction, the reversibility of image and secret data can be guaranteed. The utilization of correlation between neighb
44#
發(fā)表于 2025-3-29 05:57:08 | 只看該作者
A Multiple Linear Regression Based High-Accuracy Error Prediction Algorithm for Reversible Data Hidirovide a sparser prediction-error image for data embedding, and thus improves the performance of RDH. Experimental results have shown that the proposed method outperform the state-of-the-art error prediction algorithms.
45#
發(fā)表于 2025-3-29 10:58:35 | 只看該作者
46#
發(fā)表于 2025-3-29 14:13:19 | 只看該作者
47#
發(fā)表于 2025-3-29 16:32:09 | 只看該作者
48#
發(fā)表于 2025-3-29 22:26:06 | 只看該作者
49#
發(fā)表于 2025-3-30 01:43:56 | 只看該作者
50#
發(fā)表于 2025-3-30 05:23:15 | 只看該作者
Pixel-Value-Ordering Based Reversible Data Hiding with Adaptive Texture Classification and Modificat less smooth ones are embedded with a lower number of bits. The block classification is dynamically adjusted to achieve the adaptive embedding with the best trade-off between the capacity and the embedding distortion. Experimental results show that the proposed method can give a better performance over the previous PVO-based methods.
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