High-Capacity Framework for Reversible Data Hiding Using Asymmetric Numeral Systems

Abstract

Reversible data hiding (RDH) has been extensively studied in the field of multimedia security. Embedding capacity is an important metric for RDH performance evaluation. However, the embedding capacity of existing methods for independent and identically distributed (i.i.d.) gray-scale signals is still not good enough. In this paper, we propose a high-capacity RDH code construction method that employs asymmetric numeral systems (ANS) coding as the underlying coding framework. Based on the proposed framework, two RDH methods are presented. First, we propose a static RDH method that takes the constant host probability mass function (PMF) as input parameters and offers high embedding performance. Then, we give a dynamic RDH method that can eliminate the need for transmitting the host PMF in advance by designing a reversible dynamic probability calculator. The simulation results on discrete normally distributed signals demonstrate that the performance of the proposed static method is very close to the expected rate-distortion bound, and the proposed dynamic method can achieve satisfactory embedding capacity without prior knowledge of host PMF at the cost of slightly sacrificing steganographic data quality. Moreover, the experimental results on gray-scale images show that the proposed static method provides higher peak signal-to-noise ratio (PSNR) values and larger embedding capacities than some state-of-the-art methods, e.g., the embedding capacity of image Lena is as high as 3.571 bits per pixel.