利用重叠阵列进行改进的空间均值量化水印

Dima Pröfrock, M. Schlauweg, E. Müller
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引用次数: 0

摘要

提出了一种新的数字图像水印方法。为了实现对噪声、有损压缩、模糊和锐化攻击的高鲁棒性,对空间域阵列均值进行了量化处理。为了恢复嵌入的数据,不需要原始图像。基于该方法,可以实现低图像质量退化和高鲁棒性。为了减少图像的退化,我们的方法使用重叠数组来嵌入信息。该方法基于量化误差的均匀分布,利用重叠阵列的交点优化PSNR值。理论分析和实际结果表明,该方法优于非重叠阵列方法。实验结果证实了理论假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using overlapping arrays for an improved spatial mean quantization watermarking
This paper presents a new method for watermarking digital images. To achieve a high robustness to noise, lossy compression, blurring and sharpening attacks, spatial domain array mean values are quantized. To recover the embedded data, the original image is not required. Based on this approach, low image quality degradations with a high robustness can be achieved. To reduce the image degradations, our method uses overlapping arrays to embed the information. The method bases on the uniform distribution of quantization errors and uses the intersections of overlapping arrays to optimize the PSNR value. Theoretical analyses and practical results show the advantage over the non- overlapping-array method. Experimental results confirm the theoretical assumptions.
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