A new reversible data hiding scheme exploiting high-dimensional prediction-error histogram

Cai, Siren; Li, Xiaolong; Liu, Jiaying

doi:10.1109/icip.2016.7532856

Cited by 9 publications

(16 citation statements)

References 35 publications

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“…The method of Ni et al [46] constitutes a rough framework and foundation for RDH based on histogram modification, and hence has been further developed in the followup research [5,[8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]30,[48][49][50][51], In these studies, a histogram is first generated from the prediction error of pixels, and then it is modified by expansion or shifting to achieve reversible embedding. Currently, such methods, modifying the prediction error histogram (PEH), are collectively perceived as prediction error expansion (PEE).…”

Section: Further Discussion On Histograph Modification-based Approachesmentioning

confidence: 99%

“…Specifically, PEE can be implemented as histogram modification of the PEH, that is, expanding the bins of −1 and 0 and shifting the other bins to create space to ensure the reversibility. Such a paradigm has been extended to 2D-PEH (e.g., [10]), where the PEH is defined by h 2 (a, b) = |i : (e 2i−1 , e 2i ) = (a, b)|, and also 3D-PEH (e.g., [5]), where the PEH is defined as h 3 (a, b, c) = |i : (e 3i−2 , e 3i−1 , e 3i ) = (a, b, c)|.…”

Section: Prediction-error Expansionmentioning

confidence: 99%

“…As long as f (p) = ∅ for any prediction-error p and f (p) ∩ f (q) = ∅ for every two prediction-errors p and q, the reversibility of the mapping can be guaranteed. PEE has attracted considerable attention [5,[8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] since it can maintain low embedding distortion while at the same time provide sufficiently large payload in terms of high EC.…”

Section: Prediction-error Expansionmentioning

confidence: 99%

“…Moreover, we consider eight octants in the three-dimensional space for embedding, which makes better use of space (c.f. [5] which considers only the first octant for the embedding). We conduct experiments by applying our proposed method on six test images, including Lena, Baboon, Boat, Peppers, Airplane (F-16), and House.…”

Section: Hypothesismentioning

confidence: 99%

“…Reversible data hiding (RDH) not only guarantees the safe transmission of data content but also recovers the hidden data as well as the cover images [3,4]. However, most of these RDH algorithms bring permanent distortions to the original carrier during the embedding process, and these distortions are unacceptable in certain applications [5]. In order to achieve information hiding and distortion-free recovery of the original carrier, distortionfree reversible data hiding is considered [4].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

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A Study on Reversible Data Hiding Technique Based on Three-Dimensional Prediction-Error Histogram Modification and a Multilayer Perceptron

Hung

Lin

et al. 2022

Applied Sciences

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In the past few years, with the development of information technology and the focus on information security, many studies have gradually been aimed at data hiding technology. The embedding and extraction algorithms are mainly used by the technology to hide the data that requires secret transmission into a multimedia carrier so that the data transmission cannot be realized to achieve secure communication. Among them, reversible data hiding (RDH) is a technology for the applications that demand the secret data extraction as well as the original carrier recovery without distortion, such as remote medical diagnosis or military secret transmission. In this work, we hypothesize that the RDH performance can be enhanced by a more accurate pixel value predictor. We propose a new RDH scheme of prediction-error expansion (PEE) based on a multilayer perceptron, which is an extensively used artificial neural network in plenty of applications. The scheme utilizes the correlation between image pixel values and their adjacent pixels to obtain a well-trained multilayer perceptron so that we are capable of achieving more accurate pixel prediction results. Our data mapping method based on the three-dimensional prediction-error histogram modification uses all eight octants in the three-dimensional space for secret data embedding. The experimental results of our RDH scheme show that the embedding capacity greatly increases and the image quality is still well maintained.

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Section: Further Discussion On Histograph Modification-based Approachesmentioning

confidence: 99%

Section: Prediction-error Expansionmentioning

confidence: 99%

Section: Prediction-error Expansionmentioning

confidence: 99%

Section: Hypothesismentioning

confidence: 99%

Section: Introduction 1backgroundmentioning

confidence: 99%

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A Study on Reversible Data Hiding Technique Based on Three-Dimensional Prediction-Error Histogram Modification and a Multilayer Perceptron

Hung

Lin

et al. 2022

Applied Sciences

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3D PEE mapping based reversible data hiding for color images

2018

Multimed Tools Appl

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Intra-Frame Error Concealment Scheme Using 3D Reversible Data Hiding in Mobile Cloud Environment

Chen

Wang

et al. 2018

IEEE Access

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Data in mobile cloud environment are mainly transmitted via wireless noisy channels, which may result in transmission errors with a high probability due to its unreliable connectivity. For video transmission, unreliable connectivity may cause significant degradation of the content. Improving or keeping video quality over lossy channel is therefore a very important research topic. Error concealment with data hiding (ECDH) is an effective way to conceal the errors introduced by channels. It can reduce error propagation between neighbor blocks/frames comparing with the methods exploiting temporal/spatial correlations. The existing video ECDH methods often embed the motion vectors (MVs) into the specific locations. Nevertheless, specific embedding locations cannot resist against random errors. To compensate the unreliable connectivity in mobile cloud environment, in this paper, we present a video ECDH scheme using 3D reversible data hiding (RDH), in which each MV is repeated multiple times, and the repeated MVs are embedded into different macroblocks (MBs) randomly. Though the multiple embedding requires more embedding space, satisfactory trade-off between the introduced distortion and the reconstructed video quality can be achieved by tuning the repeating times of the MVs. For random embedding, the lost probability of the MVs decreases rapidly, resulting in better error concealment performance. Experimental results show that the PSNR values gain about 5dB at least comparing with the existing ECDH methods. Meanwhile, the proposed method improves the video quality significantly.Index Terms-3D RDH, video error concealment, mobile cloud, random embedding.

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A new reversible data hiding scheme exploiting high-dimensional prediction-error histogram

Cited by 9 publications

References 35 publications

A Study on Reversible Data Hiding Technique Based on Three-Dimensional Prediction-Error Histogram Modification and a Multilayer Perceptron

A Study on Reversible Data Hiding Technique Based on Three-Dimensional Prediction-Error Histogram Modification and a Multilayer Perceptron

3D PEE mapping based reversible data hiding for color images

Intra-Frame Error Concealment Scheme Using 3D Reversible Data Hiding in Mobile Cloud Environment

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