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Image Scrambling Degree Evaluation Algorithm based on Grey Relation Analysis

机译：基于灰关联分析的图像加扰度评估算法

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摘要

In order to objectively and automatically evaluate the degree of digital image scrambling, introduce the grey relation analysis theory, the paper proposes a new evaluation method of image scrambling. In the method, the definition and the feature of the ideal scrambling image are analyzed first, whose histogram is summarized at the same time. And then, the scrambling image is divided into some sub-images to construct some histogram sequences, and make these sequences be small samples sequences. Finally the gray relevancy of every two sequences using gray relation analysis is calculated to evaluate the image scrambling degree. Two kinds of experimental results indicate that compared with the method based SNR, the proposed method is not only efficient, flexible, running without the origin image involved, but also can provide with some conclusions which are consistent with the perception of human visual system.
机译：为了客观，自动地评价数字图像的扰码程度，介绍了灰色关联分析理论，提出了一种新的图像扰码评价方法。该方法首先分析了理想加扰图像的清晰度和特征，同时总结了其直方图。然后，将加扰图像分为一些子图像，以构造一些直方图序列，并使这些序列成为小样本序列。最后，利用灰度关系分析计算每两个序列的灰度相关性，以评估图像的加扰程度。两种实验结果表明，与基于SNR的方法相比，该方法不仅高效，灵活，无需原始图像即可运行，而且可以提供与人类视觉系统感知相一致的结论。

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