基于包含度理论的图像置乱程度评价研究  

Study on image scrambling degree based on fuzzy subsethood theory

作　　者：田小平[1,2] 吴成茂[1,2] 谭铁牛[2] 

机构地区：[1]西安邮电学院电子与信息工程系,陕西西安710121 [2]中国科学院自动化研究所模式识别国家重点实验室,北京100080

出　　处：《西安邮电学院学报》2009年第5期59-65,共7页Journal of Xi'an Institute of Posts and Telecommunications

基　　金：中国科学院自动化研究所模式识别国家重点实验室开放课题基金资助项目(编号:07-31-3)

摘　　要：提出了基于包含度理论的图像置乱程度评价新方法。本文首先对置乱前后图像中任意像素所对应二阶邻域系统构造一个模糊集并定义其隶属度;其次计算图像中各像素所对应二阶邻域系统模糊集及其补集之间的包含度;最后根据置乱前后两图像的包含度来构造图像置乱程度评价函数。实验结果表明,本文提出的评价方法是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。The new image scrambling degree evaluation method based on fuzzy subsethood theory is proposed. This paper firstly constructs the fuzzy set of two order neighbor system of image pixel and defines its membership, then the fuzzy subsethood measure between the fuzzy set of two order neighbor system and its fuzzy complement set is computed, finally the evaluation function of image scrambling degree is constructed by means of the fuzzy subsethood of primary image and scrambled image. Experimental results show that the proposed method is effective to describe the relation between the scrambling effect and the number of iterations in the scrambling techniques, which largely consists with human vision. For different images, when some transformation is used, this evaluation method can reflect to some extent the scrambling effects in each scrambling stage.

关 键 词：图像置乱 置乱度 模糊集 隶属度 模糊包含度 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]