Reversible audio data hiding algorithm using noncausal prediction of alterable orders

This paper presents a reversible data hiding scheme for digital audio by using noncausal prediction of alterable orders. Firstly, the samples in a host signal are divided into the cross and the dot sets. Then, each sample in a set is estimated by using the past P samples and the future Q samples as prediction context. The order P + Q and the prediction coefficients are computed by referring to the minimum error power method. With the proposed predictor, the prediction errors can be efficiently reduced for different types of audio files. Comparing with the existing several state-of-the-art schemes, the proposed prediction model with expansion embedding technique introduces less embedding distortion for the same embedding capacity. The experiments on the standard audio files verify the effectiveness of the proposed method.