Improved reversible data hiding based on PVO and adaptive pairwise embedding

Wu, Hui; Li, Xiaolong; Zhao, Yao; Ni, Rongrong

doi:10.1007/s11554-019-00867-w

Cited by 30 publications

(27 citation statements)

References 39 publications

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Section: Resultsmentioning

confidence: 99%

“…The experiments are implemented in MATLAB and the secret data is generated using pseudo-random number generators. The results of the proposed method are analysed and compared with some existing state-of-the-art methods including [7,8,14,22,25,27,37,41,42].…”

Section: Elsementioning

confidence: 99%

“…The proposed method is inclined towards achieving high ECs but not giving up on image quality. So, for performance validation on both aspects, i.e., EC and visual quality, the results are compared with the existing well-known methods [7,8,14,22,25,27,37,41,42], each of them directed to achieve either higher EC or higher image quality. Pairwise PEE [8], Sachnev et al [7], Pairwise PEE with optimal expansion path [27], RDHbin reservation [41] and enhanced pairwise IPVO [25] provide high ECs, however [7,8,25] are vulnerable to lower image quality.…”

Section: Elsementioning

confidence: 99%

“…Pairwise PEE [8], Sachnev et al [7], Pairwise PEE with optimal expansion path [27], RDHbin reservation [41] and enhanced pairwise IPVO [25] provide high ECs, however [7,8,25] are vulnerable to lower image quality. On the other hand, methods such as [14,22,37,42] using purely PVO predictors are more likely to stand out in terms of image quality, but they struggle to attain higher ECs. Hence, the choice of these methods is practically reasonable to corroborate the performance of the proposed method.…”

Section: Elsementioning

confidence: 99%

“…It is observed that the proposed method offers the highest image quality, irrespective of the EC . The gain in EC is quite significant when compared to PVO methods such as Improved PVO [14], pairwise PEE based on adaptive embedding [22], RDHblock extension [42] and multi-pass PVO based pairwise PEE [37].…”

Section: Elsementioning

confidence: 99%

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High‐quality reversible data hiding scheme using sorting and enhanced pairwise PEE

Kaur

Singh

Rani

et al. 2021

IET Image Processing

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This paper proposes a novel reversible data hiding (RDH) technique using sorting and pairwise prediction error expansion (PEE) to improve embedding capacity (EC) while retaining the quality of cover image. The proposed scheme traverses alternate pixels of the cover image in a zig‐zag order to construct two independent sets for sequential embedding. The pixels of each set are sorted in an increasing order of their rhombus mean followed by a two‐pass data embedding by dividing the sets into 1 × 3 size blocks based on some pre‐defined criteria. In pass 1, two prediction errors are calculated for the first and the last pixels using their rhombus means; and pairwise mapping is modified and exploited to embed the secret data in such a way that the value of the first pixel is either increased or remains unchanged, and the value of the last pixel is either decreased or remains unchanged. In pass‐2, the middle pixel is utilised to predict the first and last pixels and the values of the first pixel and the last pixel are either decreased or remains unchanged and either increased or remains unchanged, respectively. In contrast to some existing recovery‐based methods, the proposed pass‐2 guarantees to complement the changes made in pass‐1, thereby boosting the quality along with increased EC. The experimental results show that the proposed method achieves better embedding performance than the state‐of‐the‐art RDH techniques. More specifically, the proposed method gets an increment by an average of 0.46 dB and 1.01 dB for embedding 10,000 bits and 20,000 bits respectively over its closest prior art.

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