Abstract
Reversible watermarking can recover the original cover after watermark extraction, which is an important technique in the applications requiring high image quality. In this paper, a novel image reversible watermarking is proposed based on neural network and parity property. The retesting strategy utilizing the parity detection increases the capacity of the algorithm. Furthermore, the neural network is considered to calculate the prediction errors. Experimental results show that this algorithm can obtain higher capacity and preserve good visual quality.
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Acknowledgment
This work was supported in part by 973 Program (2011CB302204), National Natural Science Funds for Distinguished Young Scholar (61025013), National NSF of China (61073159, 61272355), Sino-Singapore JRP (2010DFA11010), Fundamental Research Funds for the Central Universities (2012JBM042).
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Ni, R., Cheng, H.D., Zhao, Y., Zhang, Z., Liu, R. (2013). Reversible Image Watermarking Based on Neural Network and Parity Property. In: Park, J., Ng, JY., Jeong, HY., Waluyo, B. (eds) Multimedia and Ubiquitous Engineering. Lecture Notes in Electrical Engineering, vol 240. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6738-6_36
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DOI: https://doi.org/10.1007/978-94-007-6738-6_36
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