Capacity Control for Prediction Error Expansion based Audio Reversible Data Hiding

This paper presents an efficient capacity control Algorithm for prediction error expansion based audio reversible data hiding. Current state-of-the-art audio reversible data hiding schemes use a simple capacity control algorithm that was first developed for image reversible data hiding. The performance of this algorithm can be improved by using a simple two threshold based approach. The two threshold approach can be easily integrated into any prediction error expansion based framework. Experimental results are provided for two such frameworks.

[1]  Jeho Nam,et al.  Reversible Watermarking Algorithm Using Sorting and Prediction , 2009, IEEE Transactions on Circuits and Systems for Video Technology.

[2]  Fei Wang,et al.  High Capacity Reversible Watermarking for Audio by Histogram Shifting and Predicted Error Expansion , 2014, TheScientificWorldJournal.

[3]  Yongjin Huo,et al.  Reversible audio watermarking algorithm using non-causal prediction , 2013, Wuhan University Journal of Natural Sciences.

[4]  Isao Echizen,et al.  Reversible Audio Information Hiding Based on Integer DCT Coefficients with Adaptive Hiding Locations , 2013, IWDW.

[5]  Gerald Schuller,et al.  Audio Data Hiding with High Data Rates Based on Intmdct , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[6]  Dinu Coltuc,et al.  Capacity control of reversible watermarking by two-thresholds embedding: Further results , 2013, International Symposium on Signals, Circuits and Systems ISSCS2013.

[7]  Jeffrey J. Rodríguez,et al.  Expansion Embedding Techniques for Reversible Watermarking , 2007, IEEE Transactions on Image Processing.

[8]  Zihao Li,et al.  Reversible audio data hiding algorithm using noncausal prediction of alterable orders , 2017, EURASIP J. Audio Speech Music. Process..

[9]  Dinu Coltuc,et al.  Capacity control of reversible watermarking by two-thresholds embedding , 2012, 2012 IEEE International Workshop on Information Forensics and Security (WIFS).