Reversible Watermarking Method Using Optimal Histogram Pair Shifting Based on Prediction and Sorting

Hwang, Hee Joon

doi:10.3837/tiis.2010.08.012

Cited by 36 publications

(45 citation statements)

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“…The result showed that the average predictor using the four vertically and horizontally neighboring pixels outperformed all predictors considered in [16]. This is the same predictor presented in [8], [14], [17] and is used as the basis of the accurate predictor proposed in this paper.…”

Section: Introductionmentioning

confidence: 78%

“…Conversely, distortion is caused by both expansion and shifting. In the case of histogram shifting, an optimal approach is proposed by Hwang and others [17] and Xuan and others [20]. In general, probability distribution of the prediction error is Laplacian and exponentially decreases from the center of the histogram.…”

Section: Introductionmentioning

confidence: 99%

“…Tai and others [18] utilized multiple peak points, and Jung and others [19] also presented an adaptively adjustable embedding level by considering the HVS to overcome these problems. The generalized histogram shifting method is proposed in [8] and [17], using two or four threshold values that determine the inner and outer region in a difference histogram presented in [6]. Thus, these approaches can fundamentally remove the need of the location map by expanding only allowed pixels within the inner region and shifting others to secure rooms for expansion.…”

Section: Introductionmentioning

confidence: 99%

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Reversible Watermark Using an Accurate Predictor and Sorter Based on Payload Balancing

Kang¹

2012

ETRI J

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A series of reversible watermarking technologies have been proposed to increase embedding capacity and the quality of the watermarked image simultaneously. The major skills include difference expansion, histogram shifting, and optimizing embedding order. In this paper, an accurate predictor is proposed to enhance the difference expansion. An efficient sorter is also suggested to find a more desirable embedding order. The payload is differently distributed into two sub-images, split like a chessboard pattern, for better watermarked image quality. Simulation results of the accurate prediction and sorter based on the payload balancing method yield generally better performance over previous methods. The gap is wide, in particular, in low payload for natural images. The peak signal-to-noise ratio improvement is around 2 dB in low payload ranges.

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Section: Introductionmentioning

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reversible Watermark Using an Accurate Predictor and Sorter Based on Payload Balancing

Kang¹

2012

ETRI J

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“…For small embedding capacities, numerous methods [7,15,21] have achieved performances that are more effective than that of Sachnev et al [1]; thus, the main goal of this paper is the achievement of an improved performance regarding a large capacity. For the smooth images that are rich in low-frequency components, the P2AR method of Dragoi and Coltuc [19] is more effective, whereas the use of the proposed method achieves a more effective performance regarding complex images that are rich in high-frequency components.…”

Section: Experiments Resultsmentioning

confidence: 99%

“…Numerous researchers have proposed advanced methods to improve upon the method of Sachnev et al, but they only succeeded with respect to a low embedding capacity [7,15,21]. Recently, Dragoi and Coltuc [19] proposed an advanced method that outperforms the method of Sachnev et al [1].…”

Section: Introductionmentioning

confidence: 99%

Reversible Data Hiding Using a Piecewise Autoregressive Predictor Based on Two-stage Embedding

Lee¹,

Hwang²,

Kim³

2016

Journal of Electrical Engineering and Technology

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-Reversible image watermarking, a type of digital data hiding, is capable of recovering the original image and extracting the hidden message with precision. A number of reversible algorithms have been proposed to achieve a high embedding capacity and a low distortion. While numerous algorithms for the achievement of a favorable performance regarding a small embedding capacity exist, the main goal of this paper is the achievement of a more favorable performance regarding a larger embedding capacity and a lower distortion. This paper therefore proposes a reversible data hiding algorithm for which a novel piecewise 2D auto-regression (P2AR) predictor that is based on a rhombus-embedding scheme is used. In addition, a minimum description length (MDL) approach is applied to remove the outlier pixels from a training set so that the effect of a multiple linear regression can be maximized. The experiment results demonstrate that the performance of the proposed method is superior to those of previous methods.

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High-Quality Reversible Data Hiding Approach Based on Evaluating Multiple Prediction Methods

Yang

Liu

Chang

et al. 2014

Information and Communication Technology

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Part 2: The 2014 Asian Conference on Availability, Reliability and Security, AsiaARES 2014International audienceReversible data hiding based on prediction methods is a good technique that can hide secret bits into cover images efficiently. In this paper, we propose a reversible data hiding method based on four candidates of prediction methods and local complexity for enhancing stego-image quality. In our proposed method, before we embed the secret message in one level, we evaluate the four prediction methods by calculating their efficiency ratios to decide which prediction method will be used. When the selected prediction method is applied, a threshold based on local complexity is used to determine which pixel should join the shifting and embedding process. Therefore, more pixels will avoid executing the process of pixel shifting. It results in stego-images with lower distortion. The experimental results show that our image quality is superior to that of other approaches at the same capacity

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Reversible Watermarking Method Using Optimal Histogram Pair Shifting Based on Prediction and Sorting

Cited by 36 publications

References 0 publications

Reversible Watermark Using an Accurate Predictor and Sorter Based on Payload Balancing

Reversible Watermark Using an Accurate Predictor and Sorter Based on Payload Balancing

Reversible Data Hiding Using a Piecewise Autoregressive Predictor Based on Two-stage Embedding

High-Quality Reversible Data Hiding Approach Based on Evaluating Multiple Prediction Methods

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