Abstract: Considering the shortcoming of Euclidean distance in factually measuring image differentia degree, and taking account of the fact that the image gray information at arbitrary position is closely associated with that of its neighbor, a new kind of image distance based on neighbor gray information was proposed, and an evaluation function of describing image scrambling quality was constructed based on this new image distance. The experimental results show that the proposed method is more effective in describing the image scrambling degree and reflecting the relation between the number of iterations in the scrambling techniques and the scrambling degree, which largely consists with human vision. Besides, for different images, the proposed evaluation method can reflect to some extent the effect of scrambling transformation in each scrambling stage.

Key words: image scrambling, scrambling degree, Euclidean distance, image distance

摘要： 针对传统欧氏距离不能真实刻画图像间差异程度的不足，考虑到图像中任意位置灰度信息与其周围邻域灰度存在紧密关系，提出一种考虑邻域灰度信息的图像距离新定义，并用其构造一种描述图像置乱效果好坏的评价函数。实验结果表明，该评价方法能够较好地刻画图像的置乱程度，反映了加密次数与置乱程度之间的关系，与人的视觉基本相符。而且对于不同的图像，该评价方法能在一定程度上反映所用的置乱变换在各置乱阶段的效果。

关键词: 图像置乱, 置乱度, 欧氏距离, 图像距离