In this paper, we propose a reversible data hiding scheme in an encrypted image based on bit-plane redundancy of prediction error. The scheme greatly improves the embedding capacity while maintaining lossless image recovery and error-free secret data extraction. Firstly, the original image is preprocessed to obtain the prediction error image. After the error matrix is divided into blocks, the corresponding block type is obtained. Secondly, the predicted error image is encrypted with stream cipher and the encryption matrix blocks are scrambled to ensure the security of the scheme. Finally, after embedding the block type value into the encrypted image, the spare room corresponding to each block was obtained, which was used to embed the secret data. The scheme makes full use of the spatial correlation of the pixels in the block, so it improves the embedding rate. By selecting 100 images in each dataset of BOSSbase and BOWS-2, when the block size is 3×3, the average embedding rate of our scheme can reach 3.56 bpp and 3.81 bpp, respectively. The performance of the proposed method is better than the other schemes with similar properties.
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.
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