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Improved Algorithm of Edge Adaptive Image Steganography Based on LSB Matching Revisited Algorithm

机译:基于LSB匹配重新判断算法的边缘自适应图像隐写算法改进算法

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In edge adaptive image steganography based on LSB matching revisited algorithm (EAMR for short in this paper), the secret message bits are embedded into those consecutive pixel pairs whose absolute difference of grey values are larger than or equal to a threshold T. Tan et al. [1] pointed out that since those adjacent pixel pairs can be located by the potential attackers, the pulse distortion introduced in the histogram of absolute difference of pixel pairs (HADPP for short in this paper) can easily be discovered, and a targeted steganalyzer for revealing this pulse distortion is presented in [1]. In this paper, we propose an improved algorithm for EAMR, in which the adjacent pixel pairs for data hiding are selected in a new random way. Thus the attackers cannot locate the pixel pairs selected for data hiding accurately, and the abnormality that exists in HADPP cannot be discovered any longer. Experimental results demonstrate that our improved EAMR (I-EAMR) can efficiently defeat the targeted steganalyzer presented by Tan et al. [1]. Furthermore, it can still preserve the statistics of the carrier image well enough to resist today's blind steganalyzers.
机译:在边缘自适应图像隐写基于LSB匹配的重新判断算法(本文短暂的SEAMR),秘密消息比特嵌入到那些连续像素对中,其灰度值的绝对差异大于或等于阈值T.Tan等人。 [1]指出,由于相邻像素对的潜在攻击者可以定位那些相邻的像素对,因此可以容易地发现在像素对的绝对差异(本文中的HADPP短路的绝对差异的直方图中引入的脉冲失真,并且有针对性的塞比特揭示该脉冲失真在[1]中呈现。在本文中,我们提出了一种改进的EAMR算法,其中以新的随机方式选择用于数据隐藏的相邻像素对。因此,攻击者无法定位为准确地隐藏的数据选择的像素对,并且不能再次发现HADPP中存在的异常。实验结果表明,我们改进的EAMR(I-EAMR)可以有效地击败由Tan等人提供的目标匍匐茎。 [1]。此外,它仍然可以保持载体图像的统计数据,足以抵抗今天的盲托莱斯克斯。

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