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Matrix Embedding Based Multiple Histograms Modification for Efficient Reversible Data Hiding
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AI
DOI：10.1109/LSP.2024.3455995.png)
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摘要
En 中文
Recently, matrix embedding (ME), a well-known steganographic technique, has been employed in reversible data hiding (RDH) for the first time, improving the performance of single histogram modification (SHM) methods. In this letter, the ME-based RDH strategy is extended from SHM to the more effective multiple histograms modification (MHM) to further improve the reversible embedding performance. The capacity-distortion model is first established in the novel scenario. Then, some theoretical results for payload partition and expansion-bins-determination are given. Finally, based on the derived theoretical investigations, an efficient RDH method with low computational complexity is proposed. Experimental results show that the proposed method can achieve better visual quality compared to some state-of-the-art methods.
Keyword:
Histograms
Distortion
Steganography
Visualization
Payloads
Optimization
Information science
Reversible data hiding
matrix embedding
multiple histograms modification
general distortion
期刊
IF:
9.6
论文数:
1.1W
被引数:
1.7W
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A Novel Reversible Data Hiding Scheme Based on Two-Dimensional Difference-Histogram Modification
PREAI
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