Encryption of medical image with most significant bit and high capacity in piecewise linear chaos graphics

Abstract

Along with the development of cloud computing, data privacy has become the focus of attention. However, the existing methods do not allow large amounts of information to be hidden in reversible ways. In this paper, a MSB prediction-based high-capacity reversible data hiding image encryption algorithm is put forward. Due to the local correlation between the pixels and their adjacent areas in a clear image, the value of adjacent two pixels are very close. For this reason, it seems reasonable to predict pixel values by using previously decrypted images, just as many image encoding and compression methods. However, in some cases, there are some errors. Therefore, the first step of the algorithm includes identifying all prediction errors in the original image and storing the information in a binary map of the error locations. After that, a high-capacity reversible data hiding method (CPHCRDH) is proposed to correct the prediction error. This method first conducts the prediction error correction before encryption, and preprocesses the original image according to the error location map to avoid all prediction errors, and then encrypts the pre-processed image. The clear image can be reconstructed without damage through MSP prediction. Finally, through the simulation experiment on three selected CT image test examples of the eyes, body and brain, it is shown that the proposed method is significantly superior to the selected contrasted algorithm in six indicators such as the horizontal and vertical correlation coefficients.