Trace Concealment Histogram-Shifting-Based Reversible Data Hiding with Improved Skipping Embedding and High-Precision Edge Predictor (ChinaMFS 2022)
Abstract
:1. Introduction
2. The Analysis of Embedding Traces Left by HS Algorithms
3. Proposed LS-ET Predictor
4. Proposed Framework for Concealing Embedding Traces
4.1. Data Hiding
4.1.1. Prediction
4.1.2. Improved Data Coding
4.1.3. Improved Skipping Embedding
- The length of side information: Lside.
- The number of embedding times: ET.
- All embedding positions {ee} and skipping positions {es}.
- Size of the original secret data.
- The length of CLM: LCLM.
- The compressed location map: CLM.
4.2. Data Extraction and Image Recovery
5. Experimental Results and Analysis
5.1. Determination of Parameters
5.1.1. Parameters for LS-ET Prediction
5.1.2. Parameter r for Data Coding
5.2. Analysis of the Simple Improvement on Data Coding
5.3. Anti-Steganalysis of the Proposed Framework
5.4. Capacity–Distortion Performance Comparison
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Original Data | Coded Data | Reduction in the Number of ‘1’s | ||||
---|---|---|---|---|---|---|
Number of Bits | Proportion of ‘0’s | Proportion of ‘1’s | Number of Bits | Proportion of ‘0’s | Proportion of ‘1’s | |
100,000 | 49.79% | 50.22% | 162,293 | 84.57% | 15.43% | 25,178 |
200,000 | 49.97% | 50.04% | 325,984 | 84.68% | 15.32% | 50,139 |
300,000 | 49.94% | 50.06% | 487,393 | 84.61% | 15.39% | 75,170 |
400,000 | 50.04% | 49.96% | 646,512 | 84.49% | 15.51% | 99,566 |
500,000 | 50.01% | 49.99% | 811,958 | 84.60% | 15.40% | 124,908 |
Algorithms | Embedding Rates (bpp) | Identification Error Rates |
---|---|---|
Traditional HS algorithm | 0.01 | 13.5% |
0.05 | 12.4% | |
0.1 | 10.7% | |
0.2 | 8.8% | |
Skipping HS algorithm | 0.01 | 15.5% |
0.05 | 11.1% | |
0.1 | 11.5% | |
0.2 | 20.4% | |
Proposed algorithm | 0.01 | 21.2% |
0.05 | 20.4% | |
0.1 | 19.7% | |
0.2 | 13.4% |
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Shi, H.; Hu, B.; Geng, J.; Ren, Y.; Li, M. Trace Concealment Histogram-Shifting-Based Reversible Data Hiding with Improved Skipping Embedding and High-Precision Edge Predictor (ChinaMFS 2022). Mathematics 2022, 10, 4249. https://doi.org/10.3390/math10224249
Shi H, Hu B, Geng J, Ren Y, Li M. Trace Concealment Histogram-Shifting-Based Reversible Data Hiding with Improved Skipping Embedding and High-Precision Edge Predictor (ChinaMFS 2022). Mathematics. 2022; 10(22):4249. https://doi.org/10.3390/math10224249
Chicago/Turabian StyleShi, Hui, Baoyue Hu, Jianing Geng, Yonggong Ren, and Mingchu Li. 2022. "Trace Concealment Histogram-Shifting-Based Reversible Data Hiding with Improved Skipping Embedding and High-Precision Edge Predictor (ChinaMFS 2022)" Mathematics 10, no. 22: 4249. https://doi.org/10.3390/math10224249
APA StyleShi, H., Hu, B., Geng, J., Ren, Y., & Li, M. (2022). Trace Concealment Histogram-Shifting-Based Reversible Data Hiding with Improved Skipping Embedding and High-Precision Edge Predictor (ChinaMFS 2022). Mathematics, 10(22), 4249. https://doi.org/10.3390/math10224249