Abstract: The asymmetric prediction error histogram algorithm can generate two asymmetric histograms that are left by the value of 0 and right by the value of 0. In the embedding process, the two histograms move in opposite directions, so that some modified pixels can be restored to the original pixels, that is, compensation and original reaction will occur. In view of this feature, the algorithm in this paper combines the multi-pair histogram translation algorithm to generate two pairs of asymmetric histograms. Through two rounds of asymmetric histogram embedding, i.e., four layers of data embedding, the probability of compensation restoration of modified pixels is increased. In addition, by studying the change range of peak points and pixel values of the original image after data embedding, all image blocks are classified, and the image blocks with high embedding probability are preferentially selected to reduce unnecessary pixel modification. Compared with other algorithms, this paper makes full use of the compensation and restoration reaction of the asymmetric histogram algorithm, combines the characteristics of the image pixel value distribution to reduce the invalid modification of pixels, and better ensures the quality of the dense image.

Key words: reversible data hiding, asymmetric histogram, multi-pair histogram, prediction error, histogram shifting