一种基于像素预测的图像可逆信息隐藏策略

基于像素点预测的可逆信息隐藏(Reversible Data Hiding,RDH)是当今一种低失真、高容量的信息隐藏策略,特别是对于差值扩展和直方图平移算法而言,准确预测可以同时提高数据容量和减小图像失真。文中提出了一种基于像素预测差的直方图平移方案。首先,采用Warped Distance算法来对像素值进行预测,并在此基础上利用图像的局部梯度来实现对像素值的更精确预测。综合上述两种策略,改进了现有的直方图平移算法,同时也给出了防止像素值在平移后溢出的建议。实验结果表明,相对于近年来的其他方案,该方案能够在保证图像质量的情况下有效提升数据嵌入量,并且通过调整数据嵌入层级,可以在具体使用该算法时针对图像质量和数据嵌入量进行权衡。这也进一步说明了利用图像的局部特性,特别是梯度与图像局部几何相似性,可以有效提升像素预测的精度,从而改善可逆信息隐藏的容量-失真性能。

Pixel Prediction Based Reversible Data Hiding Scheme for Image

The pixel prediction based reversible data hiding is an emerging and state-of-the-art technology for the low distortion and high capacity.In particular,for the prediction based difference expansion (DE) and histogram shift (HS) schemes,an accurate prediction can increase the payload and reduce the distortion simultaneously.This paper proposed a pixel prediction based histogram shift method in order to increase payload and reduce distortion.This method is designed based on the modified warped distance algorithm and the local gradient of an image,which can increase the prediction accuracy and furthermore improve the HS algorithm.Meanwhile,this paper gave some advice about how to avoid overflow after shifting the histogram.Experiments demonstrate that the proposed method outperforms the previous counterparts significantly in terms of both the prediction accuracy and the final embedding performance,and the tradeoff between the payload and the distortion can be run by modifying the embedding level as well.Moreover,the usage of local gradient and the local geometric similarity can improve the payload-distortion performance of reversible data hiding.