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Reversible Watermarking Based on Adaptive Prediction Error Expansion

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Genetic and Evolutionary Computing (ICGEC 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 834))

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Abstract

In traditional prediction error expansion (PEE) based reversible watermarking (RW), the watermark bits are embedded into the two peaks of the global prediction error histogram. This scheme ignores some bins in local histogram. To improve the utilization of prediction error, a method based on locally adaptive PEE is proposed. The original image is divided into two regions. In the first region, the image is divided into several blocks and the local prediction error histogram of each block is obtained after checkerboard prediction. Then, the two peaks in the local histogram of each block are used for watermark embedding. In the second region, the least significant bit (LSB) replacement is used to embed the auxiliary information and compressed positioning map. It is verified that, under the same image distortion, this method provides higher embedding capacity.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (NSFC) (No. 61272432) and Shandong Provincial Natural Science Foundation (No. ZR2014JL044).

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Authors and Affiliations

  1. College of Electronics Communication and Physics, Shandong University of Science and Technology, Qingdao, 266590, People’s Republic of China

    Qi Li, Bin Yan & Hui Li

  2. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, People’s Republic of China

    Jeng-Shyang Pan

Authors
  1. Qi Li
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  2. Bin Yan
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  3. Hui Li
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  4. Jeng-Shyang Pan
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Corresponding author

Correspondence to Bin Yan .

Editor information

Editors and Affiliations

  1. Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  2. Department of Computing, Mathematics, and Physics, Western Norway University of Applied Sciences, Bergen, China

    Jerry Chun-Wei Lin

  3. Changzhou College of Information Technology, Changzhou, Jiangsu, China

    Bixia Sui

  4. College of Smart Living and Management, Tajen University, Pingtung, Taiwan

    Shih-Pang Tseng

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Li, Q., Yan, B., Li, H., Pan, JS. (2019). Reversible Watermarking Based on Adaptive Prediction Error Expansion. In: Pan, JS., Lin, JW., Sui, B., Tseng, SP. (eds) Genetic and Evolutionary Computing. ICGEC 2018. Advances in Intelligent Systems and Computing, vol 834. Springer, Singapore. https://doi.org/10.1007/978-981-13-5841-8_26

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