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QIM-BASED HISTOGRAM-PRESERVING AND HIGH CAPACITY STEGANOGRAPHY FOR JPEG IMAGES

机译:基于QIM的直方图保留和用于JPEG图像的大容量象形图

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We propose a secure steganographic approach with a high capacity. We first use small neighborhoods of the original histogram to calculate the minimum remapping from a histogram to the odd-only and even-only histograms. We then employ a quantization index modulation-based odd-even embedding to preserve the histogram of each embedding subchannel. A minimum distortion remapping policy is used to decide the quantization value so the coefficient is increased or decreased according to a constant probability. Our embedding ensures the modification occurs in a small neighborhood and the details of the original histogram are maintained. We extensively compare our approach with two state-of-the-art steganographic approaches, MB1 and MB2, using Fridrich's 23-feature-based blind steganalysis tool with a linear discriminant analysis. The results show that our method achieves better embedding capacity, comparable image quality, and comparable security to MB1 and MB2.
机译:我们提出了一种具有高容量的安全隐写方法。我们首先使用原始直方图的较小邻域来计算从直方图到仅奇数和偶数直方图的最小重映射。然后,我们采用基于量化索引调制的奇偶嵌入来保留每个嵌入子通道的直方图。最小失真重新映射策略用于确定量化值,以便根据恒定概率增大或减小系数。我们的嵌入可确保在较小的邻域中进行修改,并保留原始直方图的详细信息。我们使用Fridrich基于23特征的盲隐写分析工具和线性判别分析,将我们的方法与两种最新的隐秘方法MB1和MB2进行了广泛比较。结果表明,我们的方法具有更好的嵌入能力,可比的图像质量以及与MB1和MB2相当的安全性。

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