优化块选择策略的高性能可逆信息隐藏算法

doi:10.19665/j.issn1001-2400.2023.02.012

摘要/Abstract

摘要：

块选择是改善基于像素值排序的可逆信息隐藏算法性能的关键策略,通过在波动性较小的块中优先嵌入数据,可提升相应算法的不可感知性。然而,现有计算波动值的方法准确性受限于分块大小、形状和所选用的预测器,所以设计一种可以在不同分块大小、不同分块形状、不同类型预测器下通用的计算方法就尤为重要。对于较大的或者形状不规则的分块,若用于参与扩展计算的像素空间位置相关性较弱,即使相应的块波动值较小,在实际嵌入过程中,也仍然可能导致无效平移。为了解决该问题,首先提出了一种改进的波动性定义,以同时考虑水平、竖直、双斜对角4个方向上下文像素的一致性,判断完局部邻域内相邻像素一致性后,再判断同一方向上两个邻域的整体像素一致性,提升了块选择的准确性;其次,考虑了最大值与次大值、最小值与次小值之间的切比雪夫距离,通过消减最大值或最小值像素的扩展来减少无效移位。实验结果表明,文中提出的方案可实现更好的不可感知性。

关键词: 可逆信息隐藏, 像素值排序, 块选择, 波动值计算, 切比雪夫距离

Abstract:

Block selection is a key strategy to improve the performance of pixel value ordering based reversible data hiding.By preferentially embedding data into blocks with a smaller fluctuation at first,better imperceptibility is able to be achieved.However,the accuracy of existing methods to calculate the fluctuation value is limited by the block size,shape and the selected predictor,so it is particularly important to design a calculation method that can be used under different block sizes,shapes and types of predictors.For large blocks or those irregular in shape,if the spatial position correlation of pixels used in the expansion is weak,even though the corresponding block is small in fluctuation,invalid shifting is still able to be introduced in the actual embedding process.To deal with this problem,we first propose an improved definition of fluctuation to consider the consistency of context pixels in horizontal,vertical,and bi-diagonal directions simultaneously.Once the consistency of adjacent pixels in the local neighborhood is determined,we further calculate the overall consistency of neighboring pixels in each direction,which improves the accuracy of block selection.Second,we consider the Chebyshev distance between the maximum value and the second maximum value,and that between the minimum value and the second minimum value,and reduce the invalid shift by subtracting the maximum or minimum pixel expansion.Experimental results show that our proposed scheme is able to achieve a better imperceptibility.

Key words: reversible data hiding, pixel-value-ordering, block selection, fluctuation value calculation, chebyshev distance

中图分类号:

TP309.7

周琳娜, 唐鑫, 吴正哲, 邓云腾, 李岱霖. 优化块选择策略的高性能可逆信息隐藏算法[J]. 西安电子科技大学学报, 2023, 50(2): 112-124.

ZHOU Linna, TANG Xin, WU Zhengzhe, DENG Yunteng, LI Dailin. High performance reversible data hiding with optimized block selection strategy[J]. Journal of Xidian University, 2023, 50(2): 112-124.

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图像	峰值信噪比
图像	文献[13]算法	文献[20]算法	文献[23]算法	文献[24]算法	文中算法
Lena	60.333	60.466	60.596	59.438	60.660
Baboon	53.586	54.245	54.361	53.851	54.431
Clock	64.804	64.780	65.090	63.985	65.175
Airplane	62.027	63.224	63.017	61.469	63.308
Lake	58.232	59.262	58.887	57.733	59.304
Sand	54.719	54.329	54.695	54.444	54.818
平均	58.950	59.384	59.441	58.487	59.616