Histogram-Based Reversible Information Hiding Improved by Prediction with the Variance to Enhance Image Quality

Weng, Chi-Yao; Yang, Chung-May; Fan, Chun-I; Liu, Kuan-Liang; Sun, Hung–Min

doi:10.1109/asiajcis.2013.23

Cited by 2 publications

(3 citation statements)

References 23 publications

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“…As shown in Fig. 3, our scheme has better image quality than previous works [13,15,18,23] with the same embedding capacities.…”

Section: Methodsmentioning

confidence: 71%

“…So far, many applications adopt the technique of reversible data hiding, such as military map, medical image [3,4], law text, and so on. Several reversible data hiding schemes have been proposed [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. According to those literatures, the techniques in reversible data hiding could be divided into three categories.…”

Section: Introductionmentioning

confidence: 99%

“…One is the difference expansion (DE for shorting) [8][9][10], another is histogram-based [11,12], and the other is a hybrid. Here, the hybrid reversible data hiding indicates that the developer takes the combination of DE and predicted error (PE for shorting) or histogram-based and PE into consideration, and creates other views in the reversible data hiding scheme [13][14][15][16][17][18][19][20][21][22][23]. The hybrid reversible data hiding scheme is an improvement of DE or Histogram-based.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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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“…As shown in Fig. 3, our scheme has better image quality than previous works [13,15,18,23] with the same embedding capacities.…”

Section: Methodsmentioning

confidence: 71%