Reversible data hiding based on histogram modification of prediction-error

Enhanced pairwise IPVO-based reversible data hiding scheme using rhombus context

In this paper, based on the principle of Code Division Multiple Access (CDMA), a novel reversible data hiding scheme is presented. The to-be-embedded data are represented by different orthogonal spreading sequences and embedded into a cover image while degrading the image quality slightly. According to the feature of orthogonality, different spreading sequences are repeatedly embedded into the image without disturbing each other, and most elements of different spreading sequences are mutually cancelled in the process of multilevel data embedding. Thus, it keeps the distortion of the embedded image at a relatively low level even with a high embedding capacity. Moreover, the location-map of the proposed scheme can be highly compressed and thus the size is quite small; it further helps to obtain high net embedding capacity. Experimental results have demonstrated that the CDMA based reversible data hiding scheme can achieve higher image quality at the moderate-to-high embedding capacity than other state-of-the-art reversible data hiding works.

The pixel-based pixel value ordering (PPVO) which each pixel is predicted using its sorted context pixels greatly improves the embedding capacity compared with the traditional PVO algorithm. In the PPVO algorithm, the prediction value is more accurate if there is a strong correlation between the target pixel and its context pixels. Otherwise, the prediction value is inaccurate. For higher embedding capacity and image quality, an improved PPVO is proposed. In the proposed scheme, the target pixel is predicted by a specific prediction method first. Then, the predicted value is added to the context pixels as the additional pixel value. In the process of embedding data, the target pixel is predicted by using the maximum / minimum value of the context pixel vector. Experimental results demonstrate that the embedding capacity of proposed method is larger than that of PPVO. The marked image quality of proposed method is also better than that of PPVO.

Adaptive embedding combining LBE and IBBE for high-capacity reversible data hiding in encrypted images

With the convenient and rapid development of cloud storage, data privacy violations have become increasingly prominent. Reversible Data Hiding (RDH) can be used to embed additional data in encrypted data stored in the cloud. Most encrypted RDH algorithms are performed in uncompressed images and are not widely employed in popular JPEG images. Therefore, an effective RDH scheme in encrypted JPEG images is proposed in the paper. This algorithm first extracts the distribution characteristics of DCT coefficients, and chaotic encryption is utilized to encrypt the DC coefficients. Then the number of AC coefficients “0” is calculated in each DCT block to generate the embedded sequence in descending order. The paillier encryption and the homomorphic encryption is employed the multiplication feature to embed for the AC coefficient. During the embedding process, the range of the encrypted ciphertexts is determined according to the paillier parameter and the embedding threshold. It ensures that the ciphertexts do not out the range of the DCT coefficient while maintaining a small file increment. The experimental results show that the scheme effectively improves the data embedding capacity and image encryption quality compared to other state-of-the-art encrypted RDH schemed. The scheme also realizes the synchronization of data extraction between the ciphertext image and the original image. The experimental analysis further shows that this scheme has high embedding capacity and good image quality. The scheme can be applied to application scenarios with high embedded capacity and high-security requirements.KeywordsDCT coefficientChaotic encryptionPaillier homomorphic encryptionReversible data hiding

The goal of image steganographic methods considers three main key issues: high embedding capacity, good visual symmetry/quality, and security. In this paper, a hybrid data hiding method combining the right-most digit replacement (RMDR) with an adaptive least significant bit (ALSB) is proposed to provide not only high embedding capacity but also maintain a good visual symmetry. The cover-image is divided into lower texture (symmetry patterns) and higher texture (asymmetry patterns) areas and these textures determine the selection of RMDR and ALSB methods, respectively, according to pixel symmetry. This paper has three major contributions. First, the proposed hybrid method enhanced the embedding capacity due to efficient ALSB utilization in the higher texture areas of cover images. Second, the proposed hybrid method maintains the high visual quality because RMDR has the closest selection process to generate the symmetry between stego and cover pixels. Finally, the proposed hybrid method is secure against statistical regular or singular (RS) steganalysis and pixel difference histogram steganalysis because RMDR is capable of evading the risk of RS detection attacks due to pixel digits replacement instead of bits. Extensive experimental tests (over 1500+ cover images) are conducted with recent least significant bit (LSB)-based hybrid methods and it is demonstrated that the proposed hybrid method has a high embedding capacity (800,019 bits) while maintaining good visual symmetry (39.00% peak signal-to-noise ratio (PSNR)).

Adaptive and non-adaptive data hiding methods for grayscale images based on modulus function

In this paper, we propose an adaptive algorithm for reversible data hiding by employing the characteristics and pyramidal relationships of original images. The major goal of reversible data hiding is to keep the reversibility of algorithm. By use of the pyramidal structure to explore the inherent characteristics of original images, regions with different smoothness levels can be determined, and then data hiding can be performed adaptively with the pre-determined threshold for balancing the output image quality and embedding capacity. On the one hand, larger capacity can be hidden into smoother regions with limited degradation of output image quality. On the other hand, the size of location map, which serves as the side information for keeping reversibility, can be reduced for embedding into smoother or less smooth regions of original image. By carefully manipulating difference values between layers in pyramidal structure, secret information can effectively be embedded. With our method, we observe better performances over relating methods with enhanced image quality, the more embedding capacity, and comparable amount of side information for decoding. More importantly, the reversibility of our method is guaranteed, meaning that original image and secret information can both be perfectly recovered at the decoder. Simulation results demonstrate that proposed method in this paper outperforms those in conventional algorithms.

This paper proposes a new lossless data embedding algorithm on spatial domain of digital images. A single key parameter is required to embed and extract data in the algorithm instead of embedding any additional information such as the location map. A × window slides over the cover image by one pixel unit, and one bit can be embedded at each position of the window. So, the ideal embedding capacity equals to the number of pixels in an image. For further increase of embedding capacity, new weight parameters for the estimation of embedding target pixels have been used. As a result, significant increase in embedding capacity and better quality of the message-embedded image in high capacity embedding have been achieved. This algorithm is verified with simulations.

A novel reversible image data hiding scheme based on pixel value ordering and dynamic pixel block partition

Steganography is the art of hiding covert message in unsuspected digital media and is generally used in secret communication between acknowledged parties. A good approach to steganography must provide good visual quality, high embedding capacity and security. In this paper, a new data hiding scheme based on octagon shaped shells is proposed to obtain better image quality and higher embedding capacity while security is achieved by scrambling the secret image using magic square. In the proposed method, a secret digit is embedded into each cover pixel pair with the help of a reference matrix consisting of connected octagons. Experimental results show that the proposed scheme ensures higher embedding capacity and security compared with existing schemes and also provides good visual quality but also better visual perception of the stego-image.

Inter-view local texture analysis based stereo image reversible data hiding

A novel reversible data hiding scheme based on difference-histogram modification and optimal EMD algorithm

Medical imaging and information management systems require transmission and storage of medical images over the Internet. Many reversible information hiding schemes for image have been proposed to ensure security and availability. In order to avoid the risk of medical information leakage and the medical image distortion, a reversible information hiding scheme based on interpolation and histogram shift for medical images has been proposed in this paper. The proposed adaptive interpolation between neighbor pixels (AIA) technique is used to obtain seed and non-seed pixels, which ensures the reversibility of the scheme while balancing the embedding capacity and the quality of marked image. Then, the image is divided into the region of interest (ROI) and the region of non-interest (NROI). Sensitive information such as electronic patient records (EPR) and electronic signatures of medical images are embedded as secret information. In the ROI, the corresponding bit histogram shift repeated embedding method (CBHSR) is adopted for embedding information to effectively avoid the problem of image distortion caused by histogram stretching. Experimental results show that algorithm not only has high embedding capacity, but also keeps the peak signal-to-noise ratio above 50dB, visual information fidelity and structural similarity above 0.99, which has good subjective and objective image quality.

An adaptive data hiding scheme with high embedding capacity and visual image quality based on SMVQ prediction through classification codebooks