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Adaptive image steganography based on pixel selection

机译:基于像素选择的自适应图像隐写术

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In image steganography, embedding data in texture image regions will cause less distortion than smooth ones. An efficient strategy to enhance the resistance capability to steganalysis is exploiting the texture image regions for steganography. In this paper, an adaptive image steganographic scheme based on pixel selection and syndrome-trellis codes (STCs) is proposed. With the measurement design of image block complexity, image blocks with larger block complexity is selected, and we have proved that each selected image block can still satisfy the selection criteria after modification, which ensures the success of information extraction. Then, a modified HUGO single-letter distortion definition is incorporated with STCs to embed the secret message bits in Least Significant Bit (LSB) planes of the selected pixels, the modification direction is determined with the block complexity. The experimental results show that the proposed steganographic scheme can perform better resistance capability to typical steganalysis tool than EALSBMR and HUGO without correction.
机译:在图像隐写术中,纹理图像区域中的嵌入数据将导致比光滑的更少的失真。一种有效的策略来提高塞加帕分析的阻力能力正在利用纹理图像区域。本文提出了一种基于像素选择和综合征 - 格子码(STC)的自适应图像隐写方案。随着图像块复杂度的测定设计,具有较大的块复杂度的图像块被选择,并且我们已经证明,每个所选择的图像块仍然能够满足修改,这确保信息提取成功后的选择标准。然后,将修改的Hugo单字母失真定义结合到STC以嵌入所选像素的最低有效位(LSB)平面中的秘密消息比特,通过块复杂度确定修改方向。实验结果表明,所提出的书签方案可以比EALSBMR和Hugo在没有校正的情况下对典型的隐星分析工具进行更好的阻力能力。

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