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An intelligent chaotic embedding approach to enhance stego-image quality

机译:一种智能混沌嵌入方法,可提高隐身图像的质量

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Steganography's role in secret communication extends from concealing information to communication. As one of several possible approaches to embed confidential information in digital images, the Least Significant Bit (LSB) technique has been widely used; however, maintaining the imperceptibility of the stego-image is still a serious concern. In this paper, an Adaptive Random (AR) k-bit embedding approach has been attempted to enhance the quality of stego-images. The original cover is divided into nonoverlapping blocks of equal size. The encrypted confidential data are embedded in each block through four different random walks. The best random walk, which provides the minimum degradation for a particular block, is identified, and is fixed for that block. The decision on the fixed random walk for each block is recorded and kept as the secret key. The AR method has also been combined with the Inverted Pattern approach, referred to as the Adaptive Random Inverted Pattern (ARIP) approach, to further enhance the quality of the stego-image. The estimated Peak Signal to Noise Ratio (PSNR) value for the ARIP method yields 1 dB enhancement.
机译:隐秘术在秘密通信中的作用从隐藏信息扩展到通信。作为在数字图像中嵌入机密信息的几种可能的方法之一,最低有效位(LSB)技术已得到广泛使用。然而,保持隐身图像的隐蔽性仍然是一个严重的问题。在本文中,尝试了一种自适应随机(AR)k位嵌入方法来提高隐身图像的质量。原始封面分为相等大小的非重叠块。加密的机密数据通过四个不同的随机游动嵌入到每个块中。确定最佳随机游走,该随机游走为特定块提供最小的降级,并针对该块固定。记录关于每个块的固定随机游动的决定,并将其保留为秘密密钥。 AR方法也已与反向模式方法(称为自适应随机反向模式(ARIP)方法)相结合,以进一步提高隐身图像的质量。 ARIP方法的估计峰值信噪比(PSNR)值可提高1 dB。

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