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A chaotic mapbased adaptive variable-size LSB method with pixel-value differencing and modulus function

机译:具有像素值差分和模函数的基于混沌映射的自适应变大小LSB方法

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摘要

In this paper, we present a least significant bit (LSB) hiding scheme that can embed variable-size secrets in LSB planes using the block-based chaotic map, adaptive difference range division, pixel-value differencing and modulus function. In particular, the block-based chaotic map in our framework is used to rearrange the locations of image blocks such that the transformed image can have more complex content than the original image; more precisely, the transformed image's inter-blocks have the low correlations while its intra-blocks have the high correlations. In addition, the adaptive division for difference range and pixel-value differencing are applied to separate smooth areas from edge areas for hiding different amounts of secrets in the pixels with the modulus function. The result of the proposed scheme is that the pixels located in the inter-blocks hide more secrets to enlarge the embedding capacity, and those located in the intra-blocks have fewer embedded secrets to maintain good visual quality. The effectiveness of our scheme is provided in experiments. The experimental results demonstrate that the proposed scheme is superior to the previous methods in providing a better embedding capacity with a good visual quality of the stego-image.
机译:在本文中,我们提出了一种最低有效位(LSB)隐藏方案,该方案可以使用基于块的混沌映射,自适应差异范围划分,像素值差分和模量函数在LSB平面中嵌入可变大小的秘密。特别是,在我们的框架中,基于块的混沌映射用于重新排列图像块的位置,以使转换后的图像比原始图像具有更复杂的内容;更准确地说,变换后的图像的块间相关性低,而其内部块相关性高。另外,用于差异范围和像素值差异的自适应划分被应用于从边缘区域分离平滑区域,以利用模数函数在像素中隐藏不同数量的秘密。所提出的方案的结果是,位于块间的像素隐藏更多秘密以扩大嵌入能力,而位于块内的像素具有较少的嵌入秘密以保持良好的视觉质量。实验证明了该方案的有效性。实验结果表明,所提出的方案在提供更好的嵌入能力和良好的隐身图像视觉质量方面优于先前的方法。

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