Improved PVO-based reversible data hiding
This paper presents an improved method for reversible data hiding based on pixel-value ordering (PVO) and prediction-error expansion (PEE). The proposed scheme involves dividing the host image into non-overlapping blocks and constructing a location map to guide data embedding, ensuring minimal distortion. Experimental results demonstrate that larger block sizes lead to better peak signal-to-noise ratios (PSNR) and lower maximum embedding changes. The technique prioritizes flat blocks to achieve higher embedding performance while maintaining high fidelity in the reconstructed images.
Improved PVO-based reversible data hiding
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Presentation Transcript
Improved PVO-based reversible data hiding Source: Digital Signal Processing, 2014 Authors: Fei Peng, Xiaolong Li,ng Reporter: Min-Hao Wu
Outline • Related Work • Proposed Scheme • Experimental Results • Conclusions
Related work • High-fidelity reversible data hiding scheme based on pixel-value-ordering and prediction-error expansion • Signal Processing • Xiaolong Li, Jian Li, Bin Li, Bin Yang
Data embedding procedure • Step1: Divide the host image into k non-overlapped blocks {X1, ... ,Xk} • Step2: The overflow/underflow location map LM is defined in this step. (Location map construction) • embed the databits into the host image • if LM(i)= 1, the overflow/underflow would occur andwe do nothing • if LM(i)= 0, and Xn-1 – X2 >= T, we do nothing • if LM(i)= 0, and Xn-1 – X2 < T, will be shifted or expanded to carry data
Take 2 × 2 sized blocks as an example • the histogram of PEmax for the Lena image that capacity about 15,000 bits by PVO-based predictor method • the bin with PEmax = 1 is usually the histogram peak
Experimental results • the performance on PSNR is better for a larger block size. • larger sized blocks provide lower maximum EC.
Conclusion • based on ordering the pixel values in image block, an effective predictor is proposed for PEE. • the flat blocks are priory selected to embed data, which is helpful to improve the embedding performance. • This method can achieve a higher PSNR under the same EC.
