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Reversible data hiding based on the local smoothness estimator and optional embedding strategy in four prediction modes

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Abstract

Four new prediction modes are proposed in this paper, each of which is a three-step process for all to-be-embedded pixels (nearly three-fourths of all the pixels). By designing each mode reasonably, all to-be-embedded pixels can be predicted with high accuracy, and thus, the number of embeddable pixels can be increased largely. In each step, a local smoothness estimator is utilized to determine if one embeddable pixel is located in a smooth or complex region, which is defined as the variance of the total neighbors of this pixel. In fact, the correlation evaluated by using the total neighbors, instead of a part, can reflect the complexity of the region more accurately. In this paper, an optional embedding strategy is introduced so as to select a low-distortion reversible data hiding (RDH) method according to the desired embedding rate (ER). Specifically, when the required ER is low, difference expansion (DE) is used to process those pixels in smooth regions while leaving the rest unaltered. With ER largely increased, adaptive embedding is used to embed 2-bit into these pixels with low local variance by DE while 1-bit into the remaining ones. The experimental results also demonstrate the proposed method is effective.

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Acknowledgment

This work was supported in part by National NSF of China (No. 61201393, No. 61272498, No. 61571139), New Star of Pearl River on Science and Technology of Guangzhou (No. 2014J2200085).

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Authors and Affiliations

  1. School of Information Engineering, Guangdong University of Technology, Guangdong, People’s Republic of China

    Shaowei Weng

  2. Fujian Provincial Key Laboratory of Data Mining and Applications, Fujian University of Technology, Fujian, People’s Republic of China

    Jeng-Shyang Pan

  3. School of Computer and Software, NanJing University of Information Science & Technology, NanJing, People’s Republic of China

    Lizhi Zhou

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  1. Shaowei Weng
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  2. Jeng-Shyang Pan
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  3. Lizhi Zhou
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Correspondence to Shaowei Weng.

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Weng, S., Pan, JS. & Zhou, L. Reversible data hiding based on the local smoothness estimator and optional embedding strategy in four prediction modes. Multimed Tools Appl 76, 13173–13195 (2017). https://doi.org/10.1007/s11042-016-3693-7

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  • DOI: https://doi.org/10.1007/s11042-016-3693-7

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