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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,将数据嵌入纹理图像区域将比平滑图像区域引起更少的失真。增强对隐写分析的抵抗能力的有效策略是利用纹理图像区域进行隐写术。本文提出了一种基于像素选择和校正子格码的自适应图像隐写方案。通过对图像块复杂度的测量设计,选择了块复杂度较大的图像块,并证明了每个被选择的图像块经过修改后仍然可以满足选择标准,保证了信息提取的成功。然后,将经修改的HUGO单字母失真定义与STC结合在一起,以将秘密消息比特嵌入所选像素的最低有效位(LSB)平面中,并根据块复杂度确定修改方向。实验结果表明,所提出的隐写方案比起EALSBMR和HUGO可以更好地抵抗典型的隐写分析工具。

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