鲁棒无损信息隐藏在医学成像、法律取证、遥感等领域有广泛的应用。提出了一种鲁棒无损图像信息隐藏算法。在含密载体图像未受损情况下,正确提取秘密信息后可无损恢复原始载体图像;在含密载体图像受到一定程度JPEG2000压缩攻击后,秘密信息仍然可以被正确提取。首先将原始载体图像分块并计算每个图像块的统计量,再根据统计量绝对值的最大值选择合适的阈值对统计量进行移位,最后利用移位后的统计量来嵌入秘密信息。实验结果表明,该算法在图像视觉质量、嵌入容量和鲁棒性3个方面都具有很好的性能。与其他鲁棒无损嵌入方法相比,在图像视觉质量和鲁棒性大致相当的情况下,该算法的嵌入容量有了很大提高,表明该算法较其他算法具有明显的优势。

Robust lossless data hiding has extensive applications in medical imaging systems, law enforcement, and remote sensing. A robust lossless image data hiding scheme is proposed in this paper. The original cover image can be recovered without any distortion after the hidden data has been extracted if the stego-image remains intact, and conversely, the hidden data can still be extracted correctly if the stego-image goes through JPEG 2000 compression to some extent. First,the proposed scheme divides a cover image into a number of non-overlapping blocks and calculates the statistical quantity of each block. Then the statistical quantity values are shifted by appropriate thresholds, which are selected according to the maximum absolute value of the statistical quantity. Finally, we can embed secret bits into the blocks by using the statistical quantity values which have been shifted. Simulation results demonstrate that the proposed algorithm can achieve high performances in the visual quality of the stego-images, data embedding capacity, and robustness. Performance comparisons with other existing robust lossless data hiding schemes are provided to demonstrate the superiority of the proposed scheme in embedding capacity when keeping the visual quality and robustness at a similar level.