基于结构随机矩阵和Arnold变换的快速压缩感知数字图像加密技术
A Fast Compressive Sensing Based Digital Image Encryption Technique using Structurally Random Matrices and Arnold Transform
摘要：
提出了一种基于结构随机矩阵和Arnold变换的快速压缩感知数字图像加密方法。考虑到在任何域中要压缩的自然图像，基于快速压缩感知的方法节省了计算时间，提高了图像的质量，并且通过选择甚至25%的测量来降低数字图像的维度。首先，利用降维技术对数字图像进行压缩，使其具有置乱效果。其次，利用Arnold变换将简化后的数字图像转换为更复杂的形式。然后，复图像再次加密的双重随机相位编码过程中嵌入一个主机图像，两个随机密钥与分数傅立叶变换被用作一个秘密密钥。在接收端，利用TwIST算法恢复解密过程。实验结果包括原始图像和重建图像之间的峰峰值信噪比，以分析该技术的有效性，并证明我们提出的方法是安全的，快速的，复杂的和强大的。
英文摘要：
A new digital image encryption method based on fast compressed sensing approach using structurally random matrices and Arnold transform is proposed. Considering the natural images to be compressed in any domain, the fast compressed sensing based approach saves computational time, increases the quality of the image and reduces the dimension of the digital image by choosing even 25 % of the measurements. First, dimension reduction is utilized to compress the digital image with scrambling effect. Second, Arnold transformation is used to give the reduced digital image into more complex form. Then, the complex image is again encrypted by double random phase encoding process embedded with a host image; two random keys with fractional Fourier transform are been used as a secret keys. At the receiver, the decryption process is recovered by using TwIST algorithm. Experimental results including peak-to-peak signal-to-noise ratio between the original and reconstructed image are shown to analyze the validity of this technique and demonstrated our proposed method to be secure, fast, complex and robust.
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