A high capacity reversible data hiding scheme based on right-left shift

Medical data security is facing great challenges in medical applications due to the open internet and the semi-trusted cloud. For the sake of privacy protection and the security of medical images, this paper proposes a secure and high visual-quality framework for medical images. In this framework, a novel reversible data hiding (RDH) based on lesion extraction embeds privacy data into medical images for privacy protection and image quality improvement, homomorphic encryption based on chaotic map encrypts images for medical image security. The experiments have shown that the proposed framework increases the security of medical data and improves the visual quality of medical images significantly. The proposed RDH in this framework outperforms the other RDH methods with contrast enhancement and the proposed encryption scheme increases image security well.

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A Secure and High Visual-Quality Framework for Medical Images by Contrast-Enhancement Reversible Data Hiding and Homomorphic Encryption

To improve the visual quality and the embedding rate of the existing reversible image watermarking algorithm, an improved reversible image watermarking algorithm based on difference expansion is proposed. First, the watermark information is divided into groups, and the information value of each group is calculated. The watermark group number and the corresponding carrier image block number are mapped, and the corresponding coefficient position of each corresponding carrier block is identified according to the value of the watermark information in each group. Second, the identified location map is compressed and embedded in the original image through the difference expansion. Through circular searching the suitable pixel position, the embedding rate can be effectively improved without sacrificing any visual quality. The experimental results show that the proposed algorithm not only has high embedding rate but also has a high visual quality and can achieve full recovery of the original image. Compared with ...

https://journals.sagepub.com/doi/pdf/10.1177/1550147716686577

An improved reversible image watermarking algorithm based on difference expansion

After the extraction of hidden data, reversible data hiding (RDH) algorithms are able to completely recover the original image without any error. For the past few years, a number of RDH algorithms based on difference expansion (DE) have been developed rapidly. However, their embedding capacity (EC) and the quality of the stego images are relatively low. In this paper, a reversible data hiding algorithm based on bidirectional difference expansion was proposed. Firstly, it scans the cover image in a Z-shaped way to transform the cover image into a 1D array. Secondly, the difference between two adjacent pixels was expanded towards two directions to embed one bit into the left pixel. Thirdly, the array was transformed into a 2D matrix to obtain the stego image. After receiving the stego image, the extraction process is performed in the following three steps. Firstly, the stego image was first transformed into a 1D array in the Z-shaped way. Secondly, the difference between two adjacent pixels was compressed towards two directions to extract the embedded bits and to restore the cover 1D array. Thirdly, the cover 1D array was transformed into a 2D matrix. Besides, to improve the quality of the stego image, the range of the mean of the two embedding pixels was used to solve the issue of overflow/underflow. Experimental results show, the EC of the cover image, the quality of the stego image and the security of the secret data are improved obviously.

A reversible data hiding algorithm based on bidirectional difference expansion

In this letter, we present a reversible data hiding scheme based on histogram modification. We exploit a binary tree structure to solve the problem of communicating pairs of peak points. Distribution of pixel differences is used to achieve large hiding capacity while keeping the distortion low. We also adopt a histogram shifting technique to prevent overflow and underflow. Performance comparisons with other existing schemes are provided to demonstrate the superiority of the proposed scheme.

Reversible Data Hiding Based on Histogram Modification of Pixel Differences

Four new prediction modes are proposed in this paper, each of which is a three-step process for all to-be-embedded pixels (nearly three-fourths of all the pixels). By designing each mode reasonably, all to-be-embedded pixels can be predicted with high accuracy, and thus, the number of embeddable pixels can be increased largely. In each step, a local smoothness estimator is utilized to determine if one embeddable pixel is located in a smooth or complex region, which is defined as the variance of the total neighbors of this pixel. In fact, the correlation evaluated by using the total neighbors, instead of a part, can reflect the complexity of the region more accurately. In this paper, an optional embedding strategy is introduced so as to select a low-distortion reversible data hiding (RDH) method according to the desired embedding rate (ER). Specifically, when the required ER is low, difference expansion (DE) is used to process those pixels in smooth regions while leaving the rest unaltered. With ER largely increased, adaptive embedding is used to embed 2-bit into these pixels with low local variance by DE while 1-bit into the remaining ones. The experimental results also demonstrate the proposed method is effective.

Lizhi Zhou

Papers

Reversible data hiding based on the local smoothness estimator and optional embedding strategy in four prediction modes