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Reversible data hiding (RDH) has been extensively studied in the field ofinformation security. In our previous work [1], an explicit implementationapproaching the rate-distortion bound of RDH has been proposed. However, thereare two challenges left in our previous method. Firstly, this method suffersfrom computing precision problem due to the use of arithmetic coding, which maycause the further embedding impossible. Secondly, it had to transmit theprobability distribution of the host signals during the embedding/extractionprocess, yielding quite additional overhead and application limitations. Inthis paper, we first propose an RDH scheme that employs our recent asymmetricnumeral systems (ANS) variant as the underlying coding framework to avoid thecomputing precision problem. Then, we give a dynamic implementation that doesnot require transmitting the host distribution in advance. The simulationresults show that the proposed static method provides slightly higher peaksignal-to-noise ratio (PSNR) values than our previous work, and largerembedding capacity than some state-of-the-art methods on gray-scale images. Inaddition, the proposed dynamic method totally saves the explicit transmissionof the host distribution and achieve data embedding at the cost of a smallimage quality loss.

A Novel Reversible Data Hiding Scheme Based on Asymmetric Numeral Systems