Digital Audio Reversible Watermarking Based On Side Information Prediction And Histogram Shifting

Reversible watermarking is a technique that embeds data into a host signal while keeping it unchanged imperceptibly. Besides, the host signal can be recovered completely after extracting the embedded data. Prediction expansion and histogram shifting are two major ways for reversible watermarking. The existing prediction methods which are called causal prediction methods just use the front samples to prediction the current sample, base on this situation, we propose two non-causal prediction methods in this paper and the experimental results confirm their superiority. Besides, we proposed improved least significant bit(LSB) algorithm and improved histogram shifting algorithm to solve the decimal problem produced by non-causal prediction methods. Finally, we combine two non-causal prediction methods with two embedding algorithms. Compared with the other state-of-the-art schemes, the proposed schemes introduce less embedding distortion under the low embedded capacity. The experiments on the standard audio files verify the effectiveness of the proposed schemes.