二维非等长图像置乱变换

传统的2维图像置乱变换一般用于正方形图像处理,对宽高不等的矩形图像,需进行正方形扩展,或使用高维置乱变换阵置乱.本文对此问题做了改进,提出了一种新颖的2维非等长图像置乱变换,给出了周期存在判据,用以选择合适的置乱系数,使得在不增加额外存储空间和计算代价的基础上,可用于非等长图像置乱,并且存在可恢复周期.实验表明所提方法的有效性和可行性.

2-Dimension Non Equilateral Image Scrambling Transformation

The classic 2-dimension image scrambling is used in the equilateral image,but for the non equilateral image,it has to be expanded into equilateral image or scrambled by the high-dimension scrambling transformation matrix.To solve the problem,in this paper,a novel 2-dimension non equilateral image scrambling transformation is proposed and the periodicity existence judgment criteria are presented.Furthermore,the proper scrambling matrix coefficients are selected by the judgment criteria so that the expanded 2-dimension scrambling transformation can be used to scramble non equilateral image without extra space and cost and the recoverable periodicity exists.The experiments show the validity and feasibility of proposed scrambling transformation.