Traditional permutation schemes mostly focus on random scrambling of pixels, often neglecting the intrinsic image information that could enhance diffusion in image encryption algorithms. This paper introduces PermutEx, a feature-extraction-based permutation method that utilizes inherent image features to scramble pixels effectively. Unlike random permutation schemes, PermutEx extracts the spatial frequency and local contrast features of the image and ranks each pixel based on this information, identifying which pixels are more important or information-rich based on texture and edge information. In addition, a unique permutation key is generated using the Logistic-Sine Map based on chaotic behavior. The ranked pixels are permuted in conjunction with this unique key, effectively permuting the original image into a scrambled version. Experimental results indicate that the proposed method effectively disrupts the correlation in information-rich areas within the image resulting in a correlation value of 0.000062. The effective scrambling of pixels, resulting in nearly zero correlation, makes this method suitable to be used as diffusion in image encryption algorithms.

翻译：传统置换方案主要关注像素的随机置乱，往往忽略了可增强图像加密算法扩散能力的图像内在信息。本文提出PermutEx方法——一种基于特征提取的置换技术，利用图像固有特征实现像素的有效置乱。与随机置换方案不同，PermutEx通过提取图像的空间频率和局部对比度特征，依据该信息对每个像素进行排序，基于纹理和边缘信息识别出重要性更高或信息量更丰富的像素。此外，基于混沌行为的Logistic-正弦映射生成唯一置换密钥。排序后的像素与该唯一密钥协同完成置换，将原始图像有效转化为置乱版本。实验结果表明，该方法能有效破坏图像信息丰富区域内的相关性，相关系数达到0.000062。这种实现近零相关性的有效像素置乱特性，使其适用于图像加密算法中的扩散环节。