Reversible data hiding using invariant pixel-value-ordering and prediction-error expansion

Ou, Bo; Li, Xiaolong; Zhao, Yao; Ni, Rongrong

doi:10.1016/j.image.2014.05.003

Cited by 139 publications

(127 citation statements)

References 38 publications

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“…whereas they are not utilized in Ou's work [28]. Extensive experiments verify that the proposed method outperforms Sachnev et al [32], and Hong et al [11].…”

Section: Resultsmentioning

confidence: 66%

“…Meanwhile, optimized embedding to obtain the best image quality by considering the embedding payoff can be achieved. Experimental results demonstrate that both the capacity and the marked image quality can be improved compared with other methods [21,30,28]. Besides, in comparison with the Sachnev et al's work [32], the proposed method also demonstrates superior performance.…”

Section: A N U S C R I P Tmentioning

confidence: 73%

“…Specifically, d 1 max is the difference between the fourth-largest pixel (p σ(n−3) ) and the maximum (p σ(n) ), considering the order of σ(n − 3) and σ(n), d 2 max is the difference between the fourth-largest pixel (p σ(n−3) ) and the second-largest pixel (p σ(n−1) ), and so on. In this way, the blocks with p σ(n) = p σ(n−1) = p σ(n−2) = p σ(n−3) can be exploited by our method to embed data by modifying d 1 max , d 2 max and d 3 max whereas they are not utilized in Ou et al's work [28].…”

Section: Improved Maximum-modification-based Data Embeddingmentioning

confidence: 99%

See 2 more Smart Citations

Reversible data hiding based on an adaptive pixel-embedding strategy and two-layer embedding

Weng

Pan

2016

Information Sciences

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“…whereas they are not utilized in Ou's work [28]. Extensive experiments verify that the proposed method outperforms Sachnev et al [32], and Hong et al [11].…”

Section: Resultsmentioning

confidence: 66%

Section: A N U S C R I P Tmentioning

confidence: 73%

Section: Improved Maximum-modification-based Data Embeddingmentioning

confidence: 99%

See 1 more Smart Citation

Reversible data hiding based on an adaptive pixel-embedding strategy and two-layer embedding

Weng

Pan

2016

Information Sciences

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“…While, a reversible data hiding scheme allows the extractor to recover the original cover media completely upon extraction of the hidden data. In the recent past, several reversible data hiding schemes have been developed based on different concepts such as lossless compression [31], difference expansion [1,112], histogram-shifting [16,30,36,40,65,96,100,110], vector quantization [13,56,68,89,98,97,101], and prediction-error [30,33,55,80,114]. A detailed review of reversible watermarking schemes is given in [46].…”

Section: Introductionmentioning

confidence: 99%

Data Hiding Schemes: A Survey

Ali¹,

Ahn²,

Pant³

2016

Gate to Computer Science and Research

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Data hiding is the process of hiding an amount of data, called secret message or watermark, into a cover media that may be audio, video, or image signal, in an imperceptible way for different purposes. Due to the advances in generation, storage, and communication technology of digital media, the necessity and importance of data hiding has drawn the attention of many researchers all over the world resulting in a lot of variants of data hiding scheme. This chapter provides a detailed review of the basic concepts of data hiding and a survey of its major variants developed so far. The chapter classifies the data hiding schemes based on several aspects of data hiding comprising artificial intelligence. Furthermore, the chapter also provides the recommendations to the interested users for further research. This review may be a useful insight and a good source for the users who are interested in the application of artificial intelligence in data hiding.

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“…A group of studies [11][12][13][14][15][16] explored neighboring pixels in an image and predicted a pixel value by its neighboring pixels. Then they adopted the histogram of predicted error for embedding messages.…”

Section: Introductionmentioning

confidence: 99%

An Information Hiding Scheme Based on Pixel-Value-Ordering and Prediction-Error Expansion with Reversibility

Lin¹,

Chen²,

Hwang³

2014

ijacsa

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Abstract-This paper proposes a data hiding scheme based on pixel-value-ordering and predication-error expansion. In a natural image, most neighboring pixels have similar pixel values, i.e. the difference between neighboring pixels is small. Based on the observation, we may predict a pixel's value according its neighboring pixels. The proposed scheme divides an image into non-overlapping blocks each of which consists of three pixels, and pixels in a block are sorted in a descending order. Messages are embedded into two difference values, where one is between the largest and medium pixels and the other is between the smallest and medium ones. In the embedding process, difference values equal to 0 or greater than 1 are unchanged or increased by 1, respectively, and those equal to 1 are also unchanged or increased by 1 if the message bit to be embedded is equal to 0 or 1, respectively. Calculating the difference value, one may extract a message bit of 0 or 1 if it is equal to 1 or 2, respectively. Recovering pixels is done by decreasing those difference values by 1 if they are equal to or larger than 2. Experimental results demonstrate that the proposed scheme may provide much larger embedding capacity, comparing to existing study, and a satisfied image quality.

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Reversible data hiding using invariant pixel-value-ordering and prediction-error expansion

Cited by 139 publications

References 38 publications

Reversible data hiding based on an adaptive pixel-embedding strategy and two-layer embedding

Reversible data hiding based on an adaptive pixel-embedding strategy and two-layer embedding

Data Hiding Schemes: A Survey

An Information Hiding Scheme Based on Pixel-Value-Ordering and Prediction-Error Expansion with Reversibility

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