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Reversible data hiding in encrypted images (RDHEI), an essential branch of reversible data hiding (RDH), has been in development for more than a decade. For most existing stream-cipher-based RDHEI algorithms, encryption schemes are often not the same; thus, these schemes have different effects on the encrypted images. As a result, it is not reasonable to compare the embedding rates (ERs) of RDHEI algorithms directly as we do for plaintext RDH algorithms. However, to our knowledge, many studies focus on the performance of embedding but neglect the influence of the encryption. To compare the performance of stream-cipher-based RDHEI algorithms more reasonably, this paper proposes a novel comprehensive measure to evaluate state-of-the-art RDHEI algorithms. First, the characteristics of the stream-cipher-based RDHEI algorithms are divided into two categories according to the encryption and embedding processes. Next, we use correlation and redundancy to evaluate the influence of encryption schemes and also use ER, computation complexity, visual quality, and algorithm stability to evaluate the embedding schemes. In the end, in order to combine all six indexes into the final evaluation measure, we standardize each index before applying the radar chart. The experimental results show the evaluation results of the recent RDHEI algorithms via a comprehensive analysis and demonstrate the guiding significance of the proposed method for the current RDHEI algorithm selection. [ABSTRACT FROM AUTHOR]

Secret sharing is a useful method which divides a secret message into several shares for security. During the recovery procedure, only when sufficient shares are obtained, the secret message can be recovered. This paper proposes two novel reversible data hiding schemes in encrypted image via secret sharing over Galois fields ${{GF}}{({p})}$ and ${{GF}}{(}{{2}^{{8}}}{)}$. The content owner first applies a specific encryption method through block and pixel permutation and Shamir’s secret sharing. Then, the theoretical demonstration is introduced to explain that the generated shares are suitable for data embedding over ${{GF}}{({p})}$ and ${{GF}}{(}{{2}^{{8}}}{)}$. Finally, two embedding algorithms over ${{GF}}{({p})}$ and ${{GF}}{(}{{2}^{{8}}}{)}$ are presented, and on the receiver side, with different keys, additional data can be extracted correctly and original image can be recovered losslessly. Experimental results show that our schemes can achieve better rate-distortion performance than some state-of-the-art schemes. [ABSTRACT FROM AUTHOR]

In recent years, the reversible data hiding with contrast enhancement (RDH-CE) technique has been proposed and developed significantly; it can perform CE for images and restore the host image losslessly. To improve the embedding rate, CE capability, and visual quality, this paper proposes a reversible CE scheme based on 2D histogram equalization, which maintains the image quality and low brightness distortion with fewer iterations and has a high embedding rate and CE capability. Specifically, to prevent image brightness distortion, the 2D histogram is separated to obtain two 2D sub-histograms before histogram shifting. The dimension with the highest embedding capacity is dynamically selected for the embedding operation in each iteration, and the two-sided histogram equalization and information embedding are performed on the separated sub-histograms. The proposed method is evaluated on two datasets, and the results show that the method has high embedding and CE capabilities with low iteration and good visualization. [Display omitted] • Perform a separation operation on the 2D histogram. • Perform two-sided 2D histogram equalization on the separated sub-histograms individually. • Select the dimension with the highest embedding capacity for embedding in each iteration. [ABSTRACT FROM AUTHOR]

[Display omitted] • Consider the effect of peak pair selection on image quality. • Select the optimal peak pair from the candidates dynamically. • Design a weighting sum function with the metric score of each peak pair as input. • Design an optimizer for the weight vector of the weighting sum function. Reversible data hiding with contrast enhancement (RDH-CE) enables contrast enhancement of the image and lossless recovery of host image after embedded data extraction. Although the current RDH-CE methods are effective in enhancing carrier images and ensuring reversibility, image quality control is still lacking, which may lead to poor image visualization. In more serious situations, the image detail information may be lost. The peak pair selection mechanism plays an extremely crucial role in image quality enhancement; however, existing work often neglects this. In this paper, we propose an RDH-CE algorithm that pursues high image quality maintenance, aiming to maintain image quality by guiding and controlling the selection of peaks and the direction of histogram shift through quality metrics. Specifically, instead of simply selecting only one pair of peaks at each peak selection stage, our algorithm selects several pairs of peaks that meet the requirements as candidate peak pairs. It then first performs simulated histogram equalization on these candidate peaks, followed by analyzing the situation of the quality metrics generated by each pair of peaks accordingly, and then selects the optimal peaks for the current iteration based on the performance of each pair of candidate peaks to be used in the equalization process. Our selection mechanism also dynamically changes the peak selection strategy based on before-and-after changes in the actual metrics, which can better ensure image quality stability over the iterations. Under the evaluations of a series of image quality metrics, the proposed method can still maintain high quality and visual effect under high iteration and has strong stability for image quality control, thus demonstrating the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

• Design a block difference model to select similar DCT blocks by combining the metrics of texture, location, and template matching. • Number of similar DCT blocks involved in Laplacian distribution estimation is selected adaptively. • Block difference threshold and the distance threshold are set further to improve the accuracy of AC coefficient distribution estimation. [Display omitted] Reversible data hiding (RDH) for JPEG images has attracted extensive attentions in recent years. As far, a number of related schemes have been proposed, which enhance the embedding performance by improving the strategies such as frequency selection and block sorting to choose appropriate embedding coefficients with the histogram shifting mechanism. Nevertheless, the existing methods do not fully consider the characteristics of DCT coefficients and lack accurate measurement on the embedding distortion. To address the above problems, we propose an improved general framework of RDH for JPEG images based on the Laplacian distribution model. The block difference model is first established for the alternating current (AC) coefficients fitting. Subsequently, the scale parameter is calculated to estimate the embedding efficiency of each AC coefficient, and the coefficients with high embedding efficiency are preferentially selected for embedding. Furthermore, the proposed framework can be combined with other JPEG RDH methods based on quantized DCT coefficient modification. Experimental results demonstrate that better performance in terms of both visual quality and file size preservation can be achieved with the proposed scheme compared with the state-of-the-art RDH schemes for JPEG images. [ABSTRACT FROM AUTHOR]

Compared to conventional reversible data hiding (RDH) methods, the dual-image RDH technique is an effective way to achieve greater embedding rate and better quality of the stego images. Motivated by the center folding-based, dual-image RDH method proposed by Lu et al. (SIGNAL PROCESSING, 115 (2015) 195–213), we propose an improved dual-image RDH method by using the selection strategy of shiftable pixels' coordinates with minimum distortion. Although the stego dual-pixel in the center folding-based method is shifted with minimum distortion, there is another shiftable pixel-coordinate that can be used without creating any extra distortion. Based on this observation, the embedding rate can be improved without any deterioration of visual quality by embedding an extra message bit into each newfound alternative pixel-coordinate. In addition, the range of parameter k , which controls the embedding rate, in our method is extended to greater than or equal to 1, therefore, a higher visual quality can be achieved when k is set at 1. The experimental results showed that the embedding rate of our method is greater than that of the center folding-based method for the same stego image quality, and our method outperforms other methods, whether in term of average PSNR or embedding rate. [ABSTRACT FROM AUTHOR]

In this paper, a color-image-dedicated reversible data hiding (RDH) algorithm is proposed to improve embedding performance by applying a guided filtering predictor and an adaptive prediction-error expansion (PEE) scheme. PEE-based RDH methods can be mainly separated into two stages for each channel embedding, i.e., pixel prediction and prediction-error histogram (PEH) modification. In our work, the inter-channel correlation is exploited at all stages of prediction and modification. Specifically, for predicting the pixels in the current channel with the guidance of pixels from other channels, a linear transform model from reference channels to the current channel is established and its coefficients are determined by the Laplacian minimization criterion. Then, to modify the PEH, an adaptive PEE embedding scheme is conducted by seeking the optimal parameters of the embedding bins and the complexity threshold to minimize distortion. The experimental results demonstrate the proposed method has better performance than the state-of-the-art, color-image RDH methods. [ABSTRACT FROM AUTHOR]

Reversible data hiding in encrypted images (RDHEI) is an essential branch of image reversible data hiding. Over the past decade, many significant achievements have been made. However, for most RDHEI researches, the cloud service user (CSU) demands either an encryption method specified by the cloud service provider (CSP) or prior knowledge about the original image to indicate the preprocessing operation. This characteristic may lead to some security issues like information leakage that may limit the use of this type of technology. To solve this problem, we propose a simple but effective RDHEI method that separates the CSU and CSP. The owner CSU exclusively sends the standard stream cipher image to the CSP, while the CSP can embed message data into the encrypted image through a simple MSB replacement without knowing the encrypted method or prior knowledge about the original image. The embedded message data can be extracted; meanwhile, the image can be approximately recovered by another authentic CSU. Since the proposed fundamental method is not error-free in most circumstances, we provide an alternative option to achieve reversibility by transmitting a perfect recovery key from the owner CSU to any authentic CSU. The experimental results demonstrate the efficacy of the proposed method. • This paper proposes an RDHEI method without any additional information transmission between the image owner and the data hider. • The security level has a significant improvement compared to the methods with preprocessing. • The proposed method improves the performance in terms of embedding and reversibility compared to the baseline methods. • The embedding performance is not influenced by the image contents, and the algorithmic complexity is decreased. [ABSTRACT FROM AUTHOR]

• This paper proposes a dual-image reversible data hiding method based on prediction-error shift. • Prediction error domain is used to explore the redundancy of the cover image content. • An elaborately designed shiftable-position model is applied with lower distortion than the existing methods. • Two high-fidelity stego images with high PSNR values are generated simultaneously. Dual-image reversible data hiding (RDH) technology has been an active research area and became an essential part of information security because of its unique advantages in security, embedding capacity and visual quality. For a dual-image RDH strategy, message data is embedded into a cover image to generate two marked images with similar visual quality. In this study, we propose an improved dual-image RDH algorithm based on a prediction-error shift strategy. As a more compact image feature, prediction error is exploited to make better use of the redundancy of image content with the maximum distortion of one. A bidirectional-shift strategy is used to extend the shiftable positions in the central zone of the allowable coordinates. Next, we design a new shiftable-position model for the prediction error corresponding to the peak value in the prediction-error histogram to embed more message bits without causing more distortion. The experimental results demonstrate the efficacy and high-fidelity of the proposed method, especially in relatively low embedding rate circumstances. The average peak signal-to-noise ratio gain of the proposed method on eight standard test images is at least 1.15 dB for the given embedding capacity of 50,000 bits compared with other state-of-the-art dual-image RDH methods. [ABSTRACT FROM AUTHOR]