This paper proposes an information hiding algorithm using matrix embedding with Hamming codes and histogram preservation in order to keep the histogram of the image unchanged before and after hiding information in digital media. First, the algorithm uses matrix embedding with Hamming codes to determine the rewriting bits of the original image, rewrite and flip them, and successfully embed the secret information. Then, according to the idea of a break-even point, a balanced pixel frequency adaptive algorithm is proposed and each embedded bit of secret information is detected and compensated by the adjacent bit of histogram data, so that the histogram change of the image before and after information hiding is minimized. At present, most of the histogram distortion values after steganography are generally over 1000 or even higher. As a contrast, the method proposed in this paper can keep the histogram distortion values to be less than 1000. The feasibility and effectiveness of the algorithm are verified by relative entropy analysis as well. The experimental results also show that the algorithm performs well in steganographic analyses of images.
Projected density matrix embedding theory with applications to the two-dimensional Hubbard model