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基于灰色关联分析的图像置乱程度评价方法


□ 马 苗 谭永杰 何雪莉

   (1.陕西师范大学 计算机科学学院, 西安 710062; 2. 西北工业大学计算机学院, 西安 710072)
  
  摘 要:为有效衡量图像置乱的程度,引入灰色理论中的灰色关联分析,提出一种新的置乱效果评价方法。该方法首先将置乱图像分块,通过计算各子块图像中每行元素的灰度均值来统计各子块的灰度信息,建立小样本序列;然后利用灰色关联分析理论计算各序列之间的灰度信息关联度来评判各子图像灰度信息的关联程度,从而获取图像的置乱效果。实验表明,该方法能有效地评价不同置乱变换的效果,且评判无须原图像参与,与基于SNR的置乱评判方法相比,能更加客观地评判置乱效果,且与人眼目测结果相符。
  关键词:图像置乱; 置乱程度; 灰色关联分析; 信噪比
  中图分类号:TP391.41; TN941.5文献标志码:A
  文章编号:1001-3695(2009)04-1595-03
  
  Image scrambling degree evaluation method based on GRA
  
  MA Miao1,2, TAN Yong-jie1 , HE Xue-li1
  
  (1. College of Computer Science, Shaanxi Normal University, Xi’an 710062, China; 2. School of Computer, Northwestern Polytechnical University, Xi’an 710072, China)
  
  Abstract:In order to evaluate the image scrambling degree effectively, introducing the grey relation analysis theory, and then suggested a new method of image scrambling. The method firstly divided the scrambled image into several blocks, then computed the average of every line pixel values in the sub-images to static the gray information sequence of each blocks, and made these sequences be small samples sequences. Finally calculated the gray relevancy of every two sequences using gray relation analysis to evaluate the image scrambling degree. Experimental results show that the method can efficiently evaluate the scrambling effect of different scrambling transformation, running without the origin image involved. Compared with SNR, it can eva-luate the scrambling effect more objectively and be consistent with the perception of human visual system. ......
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